{"title":"AI Training Courses","description":"\u003cdiv style=\"max-width: 800px; margin: 0 auto; padding: 20px;\" class=\"collection-description\"\u003e\n\u003cp\u003e\u003cstrong\u003eArtificial Intelligence is no longer the future – it's now.\u003c\/strong\u003e Whether you're an aspiring data scientist, Python developer, or business professional curious about ChatGPT and machine learning, DiviTrain helps you master AI with top-tier online training powered by Skillsoft.\u003c\/p\u003e\n\u003cp\u003eEach course in this collection offers \u003cstrong\u003ehands-on labs\u003c\/strong\u003e, \u003cstrong\u003ereal-world scenarios\u003c\/strong\u003e, and \u003cstrong\u003elive tutor support\u003c\/strong\u003e – so you can build practical skills, not just watch videos. Our AI training paths cover everything from \u003cem\u003eNeural Networks and Deep Learning\u003c\/em\u003e to \u003cem\u003eGenerative AI, Natural Language Processing (NLP)\u003c\/em\u003e, and \u003cem\u003eethical AI implementation\u003c\/em\u003e.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eFuture-proof your career with the AI training trusted by leading tech professionals worldwide. Browse the collection and start learning today.\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/div\u003e","products":[{"product_id":"machine-learning-python-course-programmer-to-architect","title":"Machine Learning With PYTHON – ML Programmer To ML Architect","description":"\u003cp data-mce-fragment=\"1\"\u003eMachine Learning Architects interpret real-time analysis of data to automate and increase efficiency across all business domains, setting the stage for meaningful AI that moves from reactive to predictive. This Journey will guide you in the transition from becoming an ML Programmer to an ML\/DL Architect Master through mechanisms such as computational theory.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eThis learning path, with more than 100 hours of online content, is divided into the following four tracks:\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eML Track 1: Machine Learning Programmer\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eML Track 2: Deep Learning Programmer\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eML Track 3: Machine Learning Engineer\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eML Track 4: Machine Learning Architect\u003c\/strong\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eTrack 1: Machine Learning Programmer\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eIn this track of the machine learning journey, the focus is linear regression, computational theory, and training sets.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eContent:\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eE-learning courses\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eNLP for ML with Python\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eLinear Algebra and Probability\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eLinear Regression Models\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eComputational Theory\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eModel Management\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eBayesian Methods\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eReinforcement Learning\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMath for Data Science \u0026amp; Machine Learning\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eBuilding ML Training Sets\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eLinear Models \u0026amp; Gradient Descent\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eOnline Mentor\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eYou can reach your Mentor 24\/7 by entering chats or submitting an email.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eFinal Exam assessment\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eEstimated duration: 90 minutes\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003ePractice Labs: \u003c\/strong\u003e\u003cstrong data-mce-fragment=\"1\"\u003eMachine Learning Programming with Python \u003c\/strong\u003e(estimated duration: 8 hours)\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003ePerform ML programming tasks with Python, such as splitting data and standardizing data, and classification using nearest neighbors and ridge regression. Then, test your skills by answering assessment questions after performing principal component analysis, visualizing correlations, training a naive Bayes model and a support vector machine model. This lab provides access to several tools commonly used in ML, including:\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMicrosoft Excel 2016, Visual Studio Code, Anaconda, Jupyter Notebook + JupyterHub, Pandas, NumPy, SiPy, Seaborn Library, Spyder IDE\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003e\u003c\/strong\u003e\u003cstrong data-mce-fragment=\"1\"\u003eTrack 2: Deep Learning Programmer\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eIn this track of the machine learning journey, the focus is neural networks, CNNs, RNNs, and ML algorithms.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eContent:\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eE-learning courses\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eGetting Started with Neural Networks\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eBuilding Neural Networks\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eTraining Neural Networks\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eImproving Neural Networks\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eConvNets\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eConvolutional Neural Networks\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eConvo Nets for Visual Recognition\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eFundamentals of Sequence Model\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eBuild \u0026amp; Train RNNs\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eML Algorithms\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003e\u003c\/strong\u003e\u003cstrong data-mce-fragment=\"1\"\u003eOnline Mentor\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eYou can reach your Mentor 24\/7 by entering chats or submitting an email.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eFinal Exam assessment\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eEstimated duration: 90 minutes\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003ePractice Labs: Deep Learning Programming with Python \u003c\/strong\u003e(estimated duration: 8 hours)\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003ePerform DL programming tasks with Python, such as performing series expansion and calculus, and work with TensorFlow and scikit-image. Then, test your skills by answering assessment questions after loading a data set for hierarchical clustering and k-means clustering, and train a model using random forests and gradient boosting.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003e\u003c\/strong\u003e\u003cstrong data-mce-fragment=\"1\"\u003eTrack 3: Machine Learning Engineer\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eIn this track of the machine learning journey, the focus is predictive modeling and analytics, ml modeling, and ml architecting.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eContent:\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eE-learning collections\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003ePredictive Modeling\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003ePlanning AI Implementation\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eML\/DL in the Enterprise\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eEnterprise Services\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eArchitecting Balance\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eEnterprise Architecture\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eRefactoring ML\/DL Algorithms\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eOnline Mentor\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eYou can reach your Mentor 24\/7 by entering chats or submitting an email.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eFinal Exam assessment\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eEstimated duration: 90 minutes\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003ePractice Labs: Architecting ML\/DL Apps with Python \u003c\/strong\u003e(estimated duration: 8 hours)\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003ePerform architecting tasks such as binning data, imputing values, performing cross validation, and evaluating a classification model. Then, test your skills by answering assessment questions after validating a model, tuning parameters, refactoring a machine learning model, and saving and loading models using Python.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eTrack 4: Machine Learning Architect\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eIn this track of the machine learning journey, the focus is applied predictive modeling, CNNs and RNNs, and ML algorithms.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eContent:\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eE-learning collections \u003c\/strong\u003e\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eApplied Predictive Modeling\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eImplementing Deep Learning\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eApplied Deep Learning\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eAdvanced Reinforcement Learning\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eML\/DL Best Practices\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eResearch Topics in ML and DL\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eDeep Learning with Keras\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eOnline Mentor\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eYou can reach your Mentor 24\/7 by entering chats or submitting an email.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eFinal Exam assessment\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eEstimated duration: 90 minutes\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003ePractice Labs: Architecting Advanced ML\/DL Apps with Python \u003c\/strong\u003e(estimated duration: 8 hours)\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003ePerform advanced ML\/DL app architecture tasks using Python, such as loading a data set to train a simple multilayer perceptron (MLP), a Convolutional Neural Network (CNN) and an LSTM model. Then, test your skills by answering assessment questions after performing image and text classification using CNN.\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":39259772616790,"sku":"","price":1199.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/21.png?v=1743543918"},{"product_id":"artificial-intelligence-ai-training-ai-apprentice-to-ai-architect-4-tracks-24-7-mentoring-labs-practice-tests-365-days-accessai-training-apprentice-to-architect-4-tracks-24-7-mentoring-live-labs-practice-tests-365-days","title":"Artificial Intelligence (AI) Training – AI Apprentice to AI Architect","description":"\u003cdiv class=\"dt-product-description-v7\"\u003e\n\u003ch2 class=\"dt-heading-xl\"\u003eAI Apprentice to AI Architect Learning Journey for Building Real-World AI Expertise\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003e\n\u003cp\u003eThe AI Apprentice to AI Architect Learning Journey is a structured four-track program that builds your skills from foundational AI theory through to enterprise-level AI system design. Across \u003cstrong\u003e57+ hours of e-learning\u003c\/strong\u003e, you work through AI development with Python, deep learning frameworks including Keras and Microsoft CNTK, Apache Spark, computer vision, Google BERT, cognitive modeling, and explainable AI. Each track includes a Final Exam assessment and 8 hours of hands-on Practice Labs, giving you practical experience with the tools AI professionals use daily. Expert tutor support is available 24\/7 throughout your 365-day access period.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-container-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eWhat this training includes\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003e\n\u003cstrong\u003e57+ hours of e-learning\u003c\/strong\u003e — 365 days access\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFinal Exam assessment per track\u003c\/strong\u003e (4 total)\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e32 hours of hands-on Practice Labs \u003c\/strong\u003e(8 hours per track)\u003c\/li\u003e\n\u003cli\u003eExpert tutor support available 24\/7\u003c\/li\u003e\n\u003cli\u003eOrganizations seeking team-wide training can explore our \u003ca href=\"https:\/\/www.divitrain.com\/pages\/for-teams\"\u003ecorporate volume solutions\u003c\/a\u003e.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-container-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eAI Engineer\u003c\/li\u003e\n\u003cli\u003eMachine Learning Engineer\u003c\/li\u003e\n\u003cli\u003eAI Developer\u003c\/li\u003e\n\u003cli\u003eData Scientist\u003c\/li\u003e\n\u003cli\u003eAI Solutions Architect\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eWhat does this learning journey cover\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eTrack 1: AI Apprentice \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThis track establishes the theoretical and practical foundations of AI. You study core AI theory, the different types of AI, human-computer interaction principles and methodologies, AI development with Python, computer vision, and cognitive modeling approaches. The 8-hour Practice Lab covers exploratory data analysis, machine learning regression and classification, deep neural networks, convolutional neural networks, and NLP text analysis using Jupyter Notebook, Python, Anaconda, Scikit-learn, and Keras.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eTrack 2: AI Developer \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThis track focuses on the frameworks and tools used in professional AI development. You work with the Microsoft Cognitive Toolkit (CNTK), Keras, Apache Spark, Amazon Machine Learning, cognitive modeling, AI in robotics, and Google BERT. The 7-hour Practice Lab puts these skills into practice through prediction models, sentiment analysis, image classification, BERT-based category classification, and prediction analysis using pySpark.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eTrack 3: AI Practitioner \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThis track advances your skills in optimizing and fine-tuning AI solutions at a production level. Topics include the role and responsibilities of an AI Practitioner, advanced CNTK functionality, the Keras framework, Apache Spark for AI development, extending Amazon Machine Learning, and building intelligent information systems. The 8-hour Practice Lab reinforces these advanced AI practitioner competencies in a real working environment.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eTrack 4: AI Architect \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThis track develops the strategic and architectural thinking required at senior AI level. You cover the elements of an AI Architect role, AI enterprise planning, AI applications across industries, reusable AI architecture patterns, evaluating current and future AI technologies and frameworks, and explainable AI (XAI). The 8-hour Practice Lab covers real-world AI Architect scenarios including implementing an AI analytics dashboard, comparing Parameter-Sharing and Federated Learning architectures, and applying AI explainability methods using Jupyter Notebook and Anaconda.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eWhere can this learning journey take your career\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eCareer paths and next training after the AI Apprentice to AI Architect journey \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eAI skills are in demand across every major industry, with organizations actively hiring across machine learning, data science, AI engineering, and enterprise AI strategy. After completing this journey, many professionals continue with \u003ca href=\"https:\/\/www.divitrain.com\/products\/machine-learning-python-course-programmer-to-architect\"\u003eMachine Learning With Python\u003c\/a\u003e to deepen their ML expertise, \u003ca href=\"https:\/\/www.divitrain.com\/products\/aws-certified-ai-practitioner-aif-c01\"\u003eAWS Certified AI Practitioner (AIF-C01)\u003c\/a\u003e to validate cloud AI knowledge, or \u003ca href=\"https:\/\/www.divitrain.com\/products\/microsoft-ai-102-azure-ai-engineer-associate\"\u003eMicrosoft AI-102: Azure AI Engineer Associate\u003c\/a\u003e to specialize in Azure-based AI solutions. For all structured multi-track programs, explore our \u003ca href=\"https:\/\/www.divitrain.com\/collections\/learning-journeys\"\u003eLearning Journeys collection\u003c\/a\u003e.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWhat prior experience do I need to start this learning journey \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThis journey is designed for technology professionals ready to move into AI development and architecture. A basic familiarity with programming concepts is helpful, particularly Python, as the early tracks include Python-based AI development. The program begins with foundational AI theory before progressing to advanced frameworks, so no prior AI-specific experience is required to start.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDoes this training prepare me for a specific AI certification exam \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThis learning journey is not tied to a single vendor certification exam. It builds broad, practical AI skills across the Microsoft, Amazon, and Google AI ecosystems, covering frameworks and tools that appear across multiple vendor certification tracks. Each track ends with a Final Exam assessment to measure your progress. For certification-specific preparation, standalone courses such as the AWS Certified AI Practitioner or Microsoft AI-102 are available separately on DiviTrain.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWhat tools and environments are used in the hands-on Practice Labs \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThe Practice Labs across all four tracks use tools that AI professionals work with in real environments. Tracks 1 and 2 use Jupyter Notebook, Python, Anaconda, Scikit-learn, and Keras for machine learning and deep learning exercises. Track 4 uses Jupyter Notebook and Anaconda for AI architecture scenarios. All labs are hosted in a cloud environment, so no local software installation is required.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIs the exam voucher included and how do I register for the exam \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThe exam voucher is not included in this training. The exam is administered globally by Pearson VUE, either at an authorized testing center or via online proctoring. Once your preparation is complete, you register and purchase your exam voucher directly through the official certification or Pearson VUE website.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eCan my team or organization get certified together \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eYes. DiviTrain offers volume licensing for teams and organizations looking to upskill at scale. Whether you are certifying a small IT team or rolling out training across departments, our corporate solutions provide flexible access and invoicing options. Visit our \u003ca href=\"https:\/\/www.divitrain.com\/pages\/for-teams\"\u003eFor Teams page\u003c\/a\u003e to learn more.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":39260323086422,"sku":"","price":1199.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/14.png?v=1743543681"},{"product_id":"aws-certified-ai-practitioner-aif-c01","title":"AWS Certified AI Practitioner AIF-C01 training","description":"\u003cdiv class=\"dt-product-description-v7\"\u003e\n  \u003ch2 class=\"dt-heading-xl\"\u003eAWS Certified AI Practitioner AIF-C01 Training\u003c\/h2\u003e\n\n  \u003cdiv class=\"dt-body-premium\"\u003e\n    The AWS Certified AI Practitioner AIF-C01 training helps learners build foundational knowledge of artificial intelligence, machine learning and generative AI within the AWS ecosystem. This training is designed for professionals who want to understand how AWS AI services support business value, practical AI use cases and responsible implementation.\n    \u003cbr\u003e\u003cbr\u003e\n    Based on the provided course content, the training supports learners who want to strengthen their understanding of AI and ML concepts, foundation models, responsible AI, AWS governance and the practical use of AWS services such as Amazon Bedrock, Amazon SageMaker and Amazon Q. It is a strong fit for business professionals, project leads, analysts and IT professionals who want a structured entry point into AWS AI.\n    \u003cbr\u003e\u003cbr\u003e\n    Please note that the certification exam voucher is not included and must be booked separately through Pearson VUE.\n  \u003c\/div\u003e\n\n  \u003cdiv class=\"dt-container-v7\"\u003e\n    \u003cdiv class=\"dt-grid-v7\"\u003e\n      \u003cdiv\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eWho is this training for\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n          \u003cli\u003eBusiness professionals and decision-makers exploring AI and ML on AWS\u003c\/li\u003e\n          \u003cli\u003eProject managers and analysts overseeing AWS-based AI initiatives\u003c\/li\u003e\n          \u003cli\u003eIT professionals looking for a structured entry point into AI on AWS\u003c\/li\u003e\n          \u003cli\u003eSales and marketing specialists who need stronger AI product understanding\u003c\/li\u003e\n          \u003cli\u003eTeams looking to build shared AWS AI knowledge across departments\u003c\/li\u003e\n        \u003c\/ul\u003e\n      \u003c\/div\u003e\n\n      \u003cdiv\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n          \u003cli\u003eAI Strategy Consultant\u003c\/li\u003e\n          \u003cli\u003eAI Project Coordinator\u003c\/li\u003e\n          \u003cli\u003eJunior AI Practitioner\u003c\/li\u003e\n          \u003cli\u003eAI Compliance Analyst\u003c\/li\u003e\n          \u003cli\u003eBusiness Intelligence Analyst\u003c\/li\u003e\n        \u003c\/ul\u003e\n      \u003c\/div\u003e\n    \u003c\/div\u003e\n  \u003c\/div\u003e\n\n  \u003ch3 class=\"dt-heading-section\"\u003eAIF-C01 Exam Domains\u003c\/h3\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eFundamentals of AI and ML \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Learn the core concepts of artificial intelligence and machine learning, including common learning approaches, the ML lifecycle and the role of AWS services in practical AI use cases.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eFundamentals of Generative AI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Build understanding of generative AI, large language models, prompt engineering, tokens and the business value of generative AI solutions within AWS environments.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eApplications of Foundation Models \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Explore how foundation models are applied in practice through AWS services such as Amazon Bedrock and Amazon Q, including evaluation, customization and use case fit.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eGuidelines for Responsible AI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Understand the principles of responsible AI, including fairness, explainability, privacy, safety and the importance of reducing bias in AI systems.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eSecurity Compliance and Governance for AI Solutions \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Learn how data privacy, access management, security controls and governance practices apply to AI and ML workloads running on AWS.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003ch3 class=\"dt-heading-section\"\u003eCareer Opportunities\u003c\/h3\u003e\n\n  \u003cdiv class=\"dt-body-premium\"\u003e\n    This training supports professionals who want to build a solid foundation in AI and generative AI on AWS without needing a deep engineering background. It is especially useful for teams that need a shared understanding of AI vocabulary, practical AWS use cases and responsible AI deployment.\n    \u003cbr\u003e\u003cbr\u003e\n    The included Practice Labs also make this training relevant for organizations that want more hands-on AWS AI learning across business and technical functions.\n    \u003cbr\u003e\u003cbr\u003e\n    For organizations looking to train multiple employees, visit \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eteam training options\u003c\/a\u003e.\n    \u003cbr\u003e\u003cbr\u003e\n    You can also explore more AWS options in the \u003ca href=\"https:\/\/www.divitrain.com\/collections\/aws-training-courses\"\u003eAWS training courses collection\u003c\/a\u003e.\n  \u003c\/div\u003e\n\n  \u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\n  \u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eIs the AIF-C01 intended for technical or non-technical professionals \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        It is designed for a broad audience and works well for both technical and non-technical learners who want foundational AWS AI knowledge.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eHow does this certification differ from AWS Certified Cloud Practitioner \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        Cloud Practitioner covers AWS Cloud broadly, while AIF-C01 focuses specifically on AI, ML, generative AI and related AWS services.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eWhat are the key AWS services covered in this training \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        Key services include Amazon Bedrock, Amazon SageMaker and Amazon Q, along with other AWS AI capabilities referenced in the current exam guide.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eDoes this course include hands-on experience with AI models \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        Yes. Based on the provided product content, this training includes Practice Labs for hands-on learning.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eIs the exam included with this training \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        No. The certification exam voucher is not included. The exam must be scheduled separately through Pearson VUE.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n  \u003c\/div\u003e\n\u003c\/div\u003e","brand":"AWS","offers":[{"title":"Default Title","offer_id":54756960174405,"sku":null,"price":329.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/AIF-C01_cd79a989-5654-48c6-b57a-c864edda2df7.webp?v=1748028571"},{"product_id":"certified-ethical-hacker-ceh-v13","title":"Certified Ethical Hacker CEH v13 Training Certification Training with Hands-On Labs","description":"\u003cdiv class=\"dt-product-description-v7\"\u003e\n\u003ch2 class=\"dt-heading-xl\"\u003ePass the CEH v13 Exam on Your First Attempt. 18 Hours of Practice Labs, Tutor Support, and MeasureUp Practice Tests Included.\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003e\n\u003cp\u003e\u003cstrong\u003eThe Certified Ethical Hacker (CEH) v13 credential by EC-Council is recognized worldwide by employers, government agencies, and defense contractors as proof that you can find and exploit vulnerabilities before real attackers do. \u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eThis CertKit delivers 24+ hours of Skillsoft video training across all 20 official exam modules, 18 hours of guided Practice Labs in a real environment, and a MeasureUp practice exam, everything structured for 312-50 exam success. Study at your own pace with 365-day access and no subscription required.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-container-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eWhat is included in this CertKit\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003e\n\u003cstrong\u003e24+ hours of Skillsoft video training\u003c\/strong\u003e covering all 20 CEH v13 exam modules, structured for exam success\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMeasureUp practice exams with 60 days access\u003c\/strong\u003e, so you know you are ready before exam day\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e18 hours of hands-on Practice Labs\u003c\/strong\u003e in a real environment with step-by-step guided exercises, so you build practical skills alongside theory\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eExpert tutor support available 24\/7\u003c\/strong\u003e, so you get answers when you are stuck, not when it is convenient for someone else\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e365-day access\u003c\/strong\u003e with no subscription and no expiry pressure\u003c\/li\u003e\n\u003cli\u003eOrganizations seeking team-wide certification can explore our \u003ca href=\"https:\/\/www.divitrain.com\/pages\/for-teams\"\u003ecorporate volume solutions\u003c\/a\u003e.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-container-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eWhy choose this CertKit over a CEH bootcamp\u003c\/h3\u003e\n\u003cp\u003eIn-person CEH bootcamps typically cost $2,500 to $3,500, require a full week out of the office, and offer no ongoing access once the week ends. This CertKit gives you the same official exam content, plus 18 hours of guided Practice Labs and expert tutor support, for a fraction of that price and with no time pressure. When you are genuinely ready, you purchase your exam voucher directly through the EC-Council or Pearson VUE website and book your exam on your own schedule.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-container-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eThis CertKit is built for you if\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eYou work in IT security and want to move into penetration testing or ethical hacking\u003c\/li\u003e\n\u003cli\u003eYou need a certification that satisfies DoD 8570 or 8140 compliance requirements\u003c\/li\u003e\n\u003cli\u003eYour employer needs evidence that you can conduct authorized security assessments\u003c\/li\u003e\n\u003cli\u003eYou are advancing from a defensive security role into offensive security\u003c\/li\u003e\n\u003cli\u003eYou want structured training with hands-on labs to prepare for the 312-50 exam\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-container-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eRoles you can pursue after CEH v13\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003ePenetration Tester\u003c\/li\u003e\n\u003cli\u003eEthical Hacker\u003c\/li\u003e\n\u003cli\u003eSecurity Analyst\u003c\/li\u003e\n\u003cli\u003eVulnerability Assessment Specialist\u003c\/li\u003e\n\u003cli\u003eInformation Security Consultant\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eWhat does the CEH v13 exam cover\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIntroduction to Ethical Hacking \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers the fundamentals of information security, the cyber kill chain, and the legal framework that separates authorized testing from criminal activity. You build the ethical hacker mindset that underpins every module that follows.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eFootprinting and Reconnaissance \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers passive and active information gathering techniques used to map a target's external attack surface without triggering alerts. You practice OSINT tools and methodologies to collect intelligence before any direct contact with a target system.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eScanning Networks \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers how to identify live hosts, open ports, and running services using tools like Nmap. Understanding network scanning lets you build an accurate picture of what is exposed and potentially vulnerable in a target environment.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eEnumeration \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers techniques to extract detailed information from systems including user accounts, network shares, and DNS records. You learn how attackers gather the specific data needed to plan a targeted exploitation attempt.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eVulnerability Analysis \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers how to identify known security weaknesses using scanning tools like Nessus and OpenVAS. You learn how to classify and prioritize vulnerabilities by severity so remediation efforts are focused where they matter most.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eSystem Hacking \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers the attack sequence from password cracking and privilege escalation through to maintaining access on a compromised system. You practice the techniques attackers use once they have an initial foothold and learn how to detect and prevent each stage.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eMalware Threats \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers the types, behaviors, and delivery mechanisms of malware including trojans, ransomware, rootkits, and fileless threats. You learn how to analyze malware behavior and understand its impact on compromised systems and networks.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eSniffing \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers network packet capture techniques including ARP poisoning and man-in-the-middle attacks used to intercept unencrypted traffic. You learn how attackers exploit network protocols and how encryption and segmentation reduce this risk.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eSocial Engineering \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers psychological manipulation tactics including phishing, vishing, and pretexting used to trick users into revealing credentials or granting unauthorized access. You learn how to identify and test an organization's human attack surface.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDenial-of-Service \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers volumetric, protocol, and application-layer DoS and DDoS attack techniques used to overwhelm services and take them offline. You learn how to evaluate system and network resilience against availability attacks.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eSession Hijacking \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers how attackers exploit weak session management to take over authenticated user sessions using techniques like token prediction and session fixation. You learn the controls that prevent session hijacking across web applications and network services.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eEvading IDS, Firewalls, and Honeypots \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers the techniques attackers use to move through an environment without triggering intrusion detection or firewall rules. You learn how to test the gaps in an organization's perimeter defenses and identify where detection can be improved.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHacking Web Servers \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers attack techniques targeting web server software including misconfigurations, outdated components, and exposed administrative interfaces. You practice footprinting web servers and identifying exploitable weaknesses that attackers scan for routinely.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHacking Web Applications \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers the OWASP Top 10 vulnerabilities and the methodology for testing web applications systematically. You learn how to identify and exploit injection flaws, broken authentication, and insecure direct object references in real application environments.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eSQL Injection \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers blind, error-based, and union-based SQL injection techniques used to extract, modify, or delete database content. You learn how to automate attacks with tools like SQLMap and how parameterized queries eliminate this class of vulnerability entirely.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHacking Wireless Networks \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers attacks on WEP, WPA, and WPA2 networks including packet capture and cracking using Aircrack-ng. You learn how rogue access points, evil twin attacks, and wireless protocol weaknesses are exploited in corporate environments.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHacking Mobile Platforms \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers Android and iOS attack surfaces including insecure data storage, improper session handling, and malicious app deployment. You learn how MDM gaps and sideloading create real security risks across enterprise mobile environments.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIoT and OT Hacking \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers security weaknesses in Internet of Things devices and operational technology environments including industrial control systems. You learn how default credentials, unpatched firmware, and exposed management interfaces create entry points in critical infrastructure.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eCloud Computing \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers attack surfaces specific to cloud environments including misconfigured storage buckets, IAM policy flaws, and serverless vulnerabilities. You learn how shared responsibility models create security gaps that penetration testers are increasingly called to assess.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eCryptography \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCovers encryption algorithms, PKI, digital signatures, and common cryptographic attacks including man-in-the-middle and padding oracle attacks. You learn how weak implementations of cryptography undermine security even when all other controls are in place.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eWhere can CEH v13 take your career\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eCareer paths and next certifications after CEH v13 \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCEH v13 is approved under DoD 8570\/8140 for IAT Level II and IAM Level II roles, making it one of the few certifications with direct government and defense contractor recognition. After CEH, many professionals move toward \u003ca href=\"https:\/\/www.divitrain.com\/products\/comptia-pentest-pt0-003\"\u003eCompTIA PenTest+ PT0-003\u003c\/a\u003e to formalize penetration testing methodology, \u003ca href=\"https:\/\/www.divitrain.com\/products\/comptia-cysa-cs0-003-comptia-cybersecurity-analyst\"\u003eCompTIA CySA+ CS0-003\u003c\/a\u003e for threat detection and analyst roles, or \u003ca href=\"https:\/\/www.divitrain.com\/products\/certified-information-systems-security-professional-cissp-2024\"\u003eCISSP\u003c\/a\u003e to move into senior security architecture. For a complete structured path, explore our \u003ca href=\"https:\/\/www.divitrain.com\/collections\/cyber-security-training\"\u003eCyber Security Training collection\u003c\/a\u003e.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWhat is the difference between CEH and CompTIA PenTest+ \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCEH v13 is a vendor-neutral certification from EC-Council that covers a broad range of attack techniques across 20 modules, with strong recognition among DoD contractors and enterprise employers. CompTIA PenTest+ focuses specifically on penetration testing methodology and reporting, with a structured exam format and broad industry acceptance. CEH is often chosen for DoD 8570 compliance requirements, while PenTest+ suits professionals who want a structured penetration testing credential recognized across the commercial sector. The two certifications complement each other well if you are building a career in offensive security.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWhat are the five phases of ethical hacking covered in the CEH v13 exam \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThe CEH exam is built around five phases: Reconnaissance (gathering information about the target), Scanning (identifying active systems and services), Gaining Access (exploiting vulnerabilities), Maintaining Access (establishing persistence), and Covering Tracks (removing evidence of the intrusion). Understanding this lifecycle helps you think through an attack from start to finish and gives you the framework employers look for in penetration testing roles. All five phases are covered directly across the exam modules included in this CertKit.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHow long is the CEH certification valid and what does renewal require \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThe CEH certification is valid for three years from the date you pass the exam. To renew, you earn EC-Council Continuing Education (ECE) credits through activities such as training, conferences, publishing, or security work. EC-Council requires a minimum number of credits over the three-year period along with a renewal fee. This ongoing renewal process ensures your credential reflects current knowledge in a rapidly evolving field.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIs the exam voucher included and how do I register for the exam \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThe exam voucher is not included in this training. The exam is administered globally by Pearson VUE, either at an authorized testing center or via online proctoring. Once your preparation is complete, you register and purchase your exam voucher directly through the official EC-Council or Pearson VUE website.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eCan my team or organization get certified together \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eYes. DiviTrain offers volume licensing for teams and organizations looking to upskill at scale. Whether you are certifying a small IT team or rolling out training across departments, our corporate solutions provide flexible access and invoicing options. Visit our \u003ca href=\"https:\/\/www.divitrain.com\/pages\/for-teams\"\u003eFor Teams page\u003c\/a\u003e to learn more.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"CEH","offers":[{"title":"Default Title","offer_id":54756965581125,"sku":null,"price":399.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/CEHv13-2.png?v=1772718865"},{"product_id":"microsoft-ai-900-microsoft-azure-ai-fundamentals","title":"Microsoft AI-900: Microsoft Azure AI Fundamentals","description":"\u003cdiv class=\"dt-product-description-v7\"\u003e\n\u003ch2 class=\"dt-heading-xl\"\u003eMicrosoft AI-900 Azure AI Fundamentals Training for Business and IT Professionals\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003e\n\u003cp\u003e\u003cstrong\u003eThe Microsoft Azure AI Fundamentals certification (AI-900) is Microsoft's entry-level credential for professionals who want to validate their understanding of AI concepts and how Azure's AI services work in practice. \u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eThis training covers all five official exam skill areas: AI workloads and responsible AI principles, machine learning on Azure, computer vision, natural language processing, and generative AI with Azure OpenAI Service, across 18+ hours of structured e-learning. It is built for business professionals, IT practitioners, developers, and consultants who want a grounding in AI fundamentals without requiring a deep technical background. Expert tutor support is available 24\/7 through the DiviTrain platform.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-container-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eWhat this training includes\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003e18+ hours of e-learning — 365 days access\u003c\/li\u003e\n\u003cli\u003eMeasureUp practice exam — 60-day access\u003c\/li\u003e\n\u003cli\u003eExpert tutor support available 24\/7\u003c\/li\u003e\n\u003cli\u003eOrganizations seeking team-wide certification can explore our \u003ca href=\"https:\/\/www.divitrain.com\/pages\/for-teams\"\u003ecorporate volume solutions\u003c\/a\u003e.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-container-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eAI Business Analyst\u003c\/li\u003e\n\u003cli\u003eTechnology Consultant\u003c\/li\u003e\n\u003cli\u003eCloud Product Manager\u003c\/li\u003e\n\u003cli\u003eDigital Transformation Lead\u003c\/li\u003e\n\u003cli\u003eIT Project Manager\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eWhat does the AI-900 exam cover\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDescribe Artificial Intelligence workloads and considerations (15–20%) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThis domain introduces the landscape of AI capabilities and the ethical principles behind responsible AI development. You will identify common AI workloads including prediction, anomaly detection, computer vision, natural language processing, document intelligence, and knowledge mining. It also covers Microsoft's six responsible AI principles — fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDescribe fundamental principles of machine learning on Azure (15–20%) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThis domain covers how machine learning models are trained, evaluated, and deployed. You will learn the difference between supervised and unsupervised learning, common task types such as regression, classification, and clustering, and how to read evaluation metrics. The domain also introduces Azure Machine Learning studio and Automated ML (AutoML) as the primary tools for building and managing ML workloads on Azure.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDescribe features of computer vision workloads on Azure (15–20%) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThis domain covers how AI systems interpret and analyse visual information, including image classification, object detection, semantic segmentation, and optical character recognition (OCR). You will explore Azure AI Vision, Azure AI Custom Vision for training domain-specific image models, and Azure AI Face for facial detection and analysis. The focus is on understanding the capabilities and appropriate use cases for each service.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDescribe features of Natural Language Processing (NLP) workloads on Azure (15–20%) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThis domain introduces how AI systems process and generate human language. Topics include text analysis, key phrase extraction, entity recognition, sentiment analysis, and language detection using Azure AI Language. You will also cover speech recognition and synthesis with Azure AI Speech and translation capabilities with Azure AI Translator, giving you a complete picture of how NLP services apply across real-world scenarios.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDescribe features of generative AI workloads on Azure (20–25%) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThis is the highest-weighted domain on the exam and reflects the growing importance of large language models in enterprise settings. You will learn what generative AI is, how large language models (LLMs) work, and how Azure OpenAI Service provides access to models like GPT for text generation, summarisation, and code writing. The domain also covers the basics of prompt engineering and Microsoft's approach to responsible generative AI deployment.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eWhere can AI-900 take your career\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eCareer paths and next certifications after AI-900 \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThe AI-900 is a Microsoft official credential that signals foundational AI literacy to employers across industries adopting Azure-based AI tools. After completing this training, many professionals build on their foundation with \u003ca href=\"https:\/\/www.divitrain.com\/products\/microsoft-az-900-microsoft-azure-fundamentals\"\u003eMicrosoft AZ-900 Azure Fundamentals\u003c\/a\u003e for broader Azure platform knowledge, or progress toward \u003ca href=\"https:\/\/www.divitrain.com\/products\/microsoft-dp-100-designing-and-implementing-a-data-science-solution-on-azure\"\u003eMicrosoft DP-100\u003c\/a\u003e for hands-on data science and machine learning work on Azure.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIs the AI-900 exam worth it for non-technical professionals \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eYes. The AI-900 is specifically designed to be accessible to professionals without a development or data science background. It validates your ability to understand AI concepts, recognise appropriate AI use cases, and work with Azure AI services at a conceptual level. For project managers, consultants, business analysts, and technology leaders involved in AI adoption decisions, it signals credibility and informed judgment in AI-related conversations.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWhat is the difference between AI-900 and AZ-900 \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThe AZ-900 (Azure Fundamentals) covers the full breadth of the Azure cloud platform including compute, networking, storage, pricing, and governance — with AI services as one component among many. The AI-900 is focused entirely on AI and machine learning concepts and how Azure's AI services are structured and used. Both are entry-level credentials with no technical prerequisites. If your primary interest is in AI, start with AI-900. If you want a broad Azure foundation first, AZ-900 is the better starting point.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDo I need any prior technical or AI knowledge to pass AI-900 \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eNo prior technical knowledge is required. The AI-900 is a conceptual exam that tests your ability to describe AI workloads, identify Azure AI services, and understand responsible AI principles — not your ability to write code or build models. Familiarity with general computing concepts is helpful, but the training is structured to take you from no prior AI knowledge through to full exam readiness across 18+ hours of e-learning.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIs the exam voucher included and how do I register for the exam \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThe exam voucher is not included in this training. The exam is administered globally by Pearson VUE, either at an authorized testing center or via online proctoring. Once your preparation is complete, you register and purchase your exam voucher directly through the official certification or Pearson VUE website.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eCan my team or organization get certified together \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eYes. DiviTrain offers volume licensing for teams and organizations looking to upskill at scale. Whether you are certifying a small IT team or rolling out training across departments, our corporate solutions provide flexible access and invoicing options. Visit our \u003ca href=\"https:\/\/www.divitrain.com\/pages\/for-teams\"\u003eFor Teams page\u003c\/a\u003e to learn more.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Microsoft","offers":[{"title":"Default Title","offer_id":54756991631685,"sku":null,"price":329.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/39_c5f7b964-594f-4a53-8bbc-024cec0ec071.png?v=1748028736"},{"product_id":"ai-and-ml-for-decision-makers","title":"AI and ML for Decision-makers","description":"\u003cp\u003e\u003cstrong\u003eUnlock Your Full Potential with DiviTrain\\'s Premier AI and ML for Decision-makers Online Training!\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003ePropel your career forward with our comprehensive AI and ML for Decision-makers course, expertly powered by Skillsoft. DiviTrain is dedicated to delivering an exceptional and effective learning journey, meticulously designed for your success in het behalen van certificering.\u003c\/p\u003e\n\u003ch3\u003eKey Advantages of Choosing DiviTrain for AI and ML for Decision-makers:\u003c\/h3\u003e\n\u003cul\u003e\n    \u003cli\u003e\n\u003cstrong\u003eComprehensive:\u003c\/strong\u003e curriculum meticulously aligned with official certification exam objectives.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eEngaging:\u003c\/strong\u003e hands-on labs and industry-leading MeasureUp practice exams to ensure real-world skill development.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eDedicated:\u003c\/strong\u003e live tutor support from certified experts, available 365 days a year to guide you.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHighly:\u003c\/strong\u003e flexible e-learning platform, allowing you to learn at your own pace, on any device, anytime, anywhere.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eWhat You Will Learn: A Glimpse into the Curriculum\u003c\/h3\u003e\n\u003cp\u003eOur structured and engaging modules will guide you through every critical aspect of AI and ML for Decision-makers:\u003c\/p\u003e\n\u003cul\u003e\n    \u003cli\u003eModule 1: Introduction to AI and ML for Decision-makers\u003c\/li\u003e\n\u003cli\u003eModule 2: Core Concepts and Architecture\u003c\/li\u003e\n\u003cli\u003eModule 3: Practical Implementation and Hands-on Labs\u003c\/li\u003e\n\u003cli\u003eModule 4: Advanced Topics and Best Practices Kennis van Technologieën\u003c\/li\u003e\n\u003cli\u003eModule 5: Certification Exam Preparation Strategies\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eIs This AI and ML for Decision-makers Course Right For You?\u003c\/h3\u003e\n\u003cp\u003eThis course is designed to meet the unique needs of diverse learners:\u003c\/p\u003e\n\u003cul\u003e\n    \u003cli\u003e\n\u003cstrong\u003eAspiring IT Starters:\u003c\/strong\u003e If you are new to IT and seeking a clear path, This AI and ML for Decision-makers course provides a clear, structured learning path, demystifying complex topics and building your foundational knowledge and confidence for a successful start in IT.\u003c\/li\u003e\n    \u003cli\u003e\n\u003cstrong\u003eAmbitious Career Switchers:\u003c\/strong\u003e If you are looking to transition into a dynamic IT role, Quickly acquire in-demand, practical skills with AI and ML for Decision-makers and earn a valuable certification that significantly boosts your resume and helps you transition smoothly into a new IT career.\u003c\/li\u003e\n    \u003cli\u003e\n\u003cstrong\u003eExperienced IT Professionals:\u003c\/strong\u003e If you aim to upgrade your skills and earn advanced certifications, Deepen your expertise in AI and ML for Decision-makers, stay ahead of the curve with the latest technologies, and validate your advanced skills with a globally recognized certification.\u003c\/li\u003e\n    \u003cli\u003e\n\u003cstrong\u003eForward-Thinking Employers (B2B):\u003c\/strong\u003e If you need to upskill your team for enhanced performance, Equip your team with standardized, high-quality training through DiviTrain. Enhance team productivity, achieve project goals effectively, and benefit from group licenses and progress reporting.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDon\\'t just learn – achieve mastery. Enroll in DiviTrain\\'s AI and ML for Decision-makers online course today and take a significant step towards your career goals!\u003c\/strong\u003e\u003c\/p\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757013389637,"sku":null,"price":299.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/ai_ML_f739b70c-55a1-4ef7-a1de-61af5f603337.webp?v=1748028864"},{"product_id":"enhancing-enterprise-security-with-generative-ai-and-artificial-intelligence","title":"Enhancing Enterprise Security with Generative AI and Artificial Intelligence","description":"\u003ch2 class=\"dt-heading-xl\"\u003eWin the AI Arms Race: Enhancing Enterprise Security with GenAI \u0026amp; AI (2026 Updated)\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003e\n    In 2026, the perimeter is no longer a physical or digital boundary—it is a cognitive one. As adversaries weaponize Large Language Models (LLMs) to industrialize phishing and create self-evolving malware, the enterprise must transition to an \u003cstrong\u003eAI-Native Defense\u003c\/strong\u003e. This elite training path provides the technical authority to integrate Generative AI and predictive machine learning into the heart of your Security Operations Center (SOC). You will move beyond simple automation to master \u003cstrong\u003eAgentic Workflows\u003c\/strong\u003e—autonomous security agents that hunt, triage, and remediate threats at machine speed. This course is the definitive guide to building a resilient, \"Secure-by-Design\" AI infrastructure while mitigating the emerging risks of prompt injection, data poisoning, and Shadow AI.\n\u003c\/div\u003e\n\n\n\n\u003cdiv class=\"dt-grid-v7\"\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eWho is this for?\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003eSecurity Architects\u003c\/strong\u003e designing the next generation of AI-driven zero-trust environments.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eSOC Managers \u0026amp; Lead Analysts\u003c\/strong\u003e tasked with reducing alert fatigue and mean-time-to-remediate (MTTR).\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eCISO \u0026amp; Risk Officers\u003c\/strong\u003e needing to govern the rapid adoption of AI while maintaining compliance (GDPR, EU AI Act).\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eSecurity Engineers\u003c\/strong\u003e looking to build automated \"Guardrails\" for enterprise GenAI deployments.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003eAI Security Architect\u003c\/li\u003e\n            \u003cli\u003eAutonomous SOC Lead\u003c\/li\u003e\n            \u003cli\u003eThreat Intelligence Engineer (AI Focus)\u003c\/li\u003e\n            \u003cli\u003eAI Risk \u0026amp; Compliance Manager\u003c\/li\u003e\n            \u003cli\u003eCognitive Security Specialist\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n\u003c\/div\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eCourse Curriculum\u003c\/h3\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eThe AI Threat Landscape: Offensive vs. Defensive AI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Analyze the \"Dark Side\" of AI. Understand how attackers use LLMs for hyper-personalized phishing, deepfake impersonation, and automated vulnerability discovery. This module establishes the strategic necessity of using AI-driven defense to counter AI-orchestrated attacks, focusing on the shift from manual signature-based detection to autonomous behavioral analysis.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eAgentic SOC: Automating Triage \u0026amp; Response \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Master the shift from tools to \u003cstrong\u003eSecurity Agents\u003c\/strong\u003e. Learn to deploy AI agents that autonomously correlate signals across your XDR\/SIEM, perform \"first-pass\" triage, and generate incident timelines in natural language. You will learn to implement \u003cstrong\u003eHuman-in-the-Loop (HITL)\u003c\/strong\u003e controls to ensure high-risk actions—like disabling a critical user account—always have a human final approval.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eSecuring the AI Pipeline: Prompt Injection \u0026amp; Data Leakage \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Protect your own AI assets. Deep dive into the \u003cstrong\u003eOWASP Top 10 for LLM Applications\u003c\/strong\u003e. Learn to defend against prompt injection, data poisoning, and unauthorized model access. Master the use of AI-SPM (AI Security Posture Management) to discover \"Shadow AI\" instances and secure the access tokens and plugins used by enterprise agents.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eAI-Driven Identity \u0026amp; Zero Trust \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Identity is the new perimeter. Learn to use machine learning to baseline \"Normal\" user and service account behavior. Master the deployment of AI-powered Multi-Factor Authentication (MFA) that detects session hijacking and token theft in real-time, enforcing Zero Trust principles through continuous, context-aware verification.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eAI Forensics \u0026amp; Continuous Compliance \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Turn weeks of investigation into minutes. Learn to use GenAI to summarize vast event logs and reconstruct attack \"kill-chain\" storylines. This module also covers \u003cstrong\u003eAutomated Compliance\u003c\/strong\u003e, showing you how to use AI to continuously audit your posture against NIST AI RMF and ISO standards, generating audit-ready reports on demand.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eWill AI replace human security analysts in 2026?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            AI won't replace analysts, but analysts who use AI will replace those who don't. In 2026, AI handles the \u003cstrong\u003e\"Routine Toil\"\u003c\/strong\u003e (log parsing, initial triage), while humans move into \u003cstrong\u003e\"Strategic Defense\"\u003c\/strong\u003e (threat hunting, policy design, and complex forensic judgment). This course focuses on that transition.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eWhat is the difference between Predictive AI and Generative AI in security?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            Predictive AI (Machine Learning) is used to \u003cstrong\u003edetect\u003c\/strong\u003e anomalies and patterns in traffic data. Generative AI is used to \u003cstrong\u003eassist\u003c\/strong\u003e the human; it writes the reports, synthesizes threat intelligence, and acts as a \"Copilot\" for the analyst to query the data using natural language.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eHow do we prevent our security AI from making mistakes (Hallucinations)?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            We use a \u003cstrong\u003eMulti-Agent Architecture\u003c\/strong\u003e and \u003cstrong\u003eRAG (Retrieval-Augmented Generation)\u003c\/strong\u003e. By forcing the AI to ground its answers in verified security logs and documentation, and by using one \"Supervisor\" agent to check the work of \"Worker\" agents, we significantly reduce errors and ensure high-fidelity outcomes.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757037998405,"sku":null,"price":349.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/aiSec_282750c3-90db-42a7-802d-06a4a2e01c09.webp?v=1773173607"},{"product_id":"generative-ai-business-transformation","title":"Generative AI Business Transformation","description":"\u003ch2 class=\"dt-heading-xl\"\u003eLead the Cognitive Enterprise: Generative AI Business Transformation (2026 Strategic Update)\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003e\n    In 2026, Generative AI is no longer a pilot project; it is the fundamental operating system of the modern enterprise. \u003cstrong\u003eGenerative AI Business Transformation\u003c\/strong\u003e is the definitive track for leaders, consultants, and strategists tasked with re-engineering organizations for an AI-first world. This elite path moves beyond the \"Chatbot\" phase to master \u003cstrong\u003eAgentic Workflows, AI-Driven Value Streams, and Cognitive Governance\u003c\/strong\u003e. You will gain the strategic authority to identify high-ROI use cases, manage the cultural shift of human-AI collaboration, and build a resilient infrastructure that turns raw data into autonomous competitive advantage.\n\u003c\/div\u003e\n\n\n\n\u003cdiv class=\"dt-grid-v7\"\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eWho is this for?\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003eC-Suite \u0026amp; Executives\u003c\/strong\u003e steering their organization through the largest technological shift since the internet.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eTransformation Leads\u003c\/strong\u003e managing the migration from legacy workflows to automated, agent-led operations.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eProduct Managers\u003c\/strong\u003e looking to embed generative intelligence into core customer-facing value propositions.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eHR \u0026amp; Operations Directors\u003c\/strong\u003e navigating the future of work and AI-augmented workforce planning.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003eChief AI Officer (CAIO)\u003c\/li\u003e\n            \u003cli\u003eAI Strategy Consultant\u003c\/li\u003e\n            \u003cli\u003eDirector of Digital Transformation\u003c\/li\u003e\n            \u003cli\u003eAI Operations (AIOps) Lead\u003c\/li\u003e\n            \u003cli\u003eEnterprise Architect (AI Focus)\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n\u003c\/div\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eCourse Curriculum\u003c\/h3\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eStrategic Alignment: The AI Capability Maturity Model \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Learn to assess your organization's AI readiness. We explore the five stages of AI maturity—from \u003cstrong\u003eAd-hoc experimentation to Fully Autonomous operations\u003c\/strong\u003e. You will learn to build a roadmap that aligns AI initiatives with core business KPIs, ensuring that transformation is driven by value, not just novelty.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eOperational Excellence: From Tasks to Agentic Workflows \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Understand the shift from \"Human-in-the-loop\" to \u003cstrong\u003eAutonomous Agents\u003c\/strong\u003e. This module covers the re-engineering of business processes (Supply Chain, Customer Service, Legal) where AI agents execute multi-step tasks, access external tools, and make data-driven decisions within defined guardrails.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eData as a Moat: RAG \u0026amp; Proprietary Intelligence \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Generic AI is a commodity; proprietary data is the advantage. Master the strategy of \u003cstrong\u003eRetrieval-Augmented Generation (RAG)\u003c\/strong\u003e and Knowledge Graphs. Learn how to securely leverage internal data assets (ERP, CRM, Knowledge Bases) to create custom AI models that speak your brand’s voice and understand your company’s unique logic.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eRisk, Ethics, \u0026amp; The AI Governance Framework \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Navigate the complexities of AI accountability. Learn to implement \u003cstrong\u003eResponsible AI (RAI)\u003c\/strong\u003e frameworks that address bias, hallucination, and data privacy. We cover the latest global regulations (like the EU AI Act) and teach you how to set up an AI Center of Excellence (CoE) to oversee safe deployment.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eHuman-Centric Change Management \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Transformation fails without people. Master the psychological and structural shift required to transition your workforce into \u003cstrong\u003e\"AI-Augmented\" roles\u003c\/strong\u003e. Learn to design training programs for prompt literacy, address job displacement concerns with upskilling, and foster a culture of relentless experimentation.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eWhat is the first step in a GenAI transformation?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            The first step is a \u003cstrong\u003eHigh-Value Use Case Audit\u003c\/strong\u003e. Instead of trying to automate everything, identify one \"pain point\" where GenAI can significantly reduce costs or increase speed (e.g., customer support or content localization). Success in one area builds the momentum and funding for enterprise-wide scaling.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eHow do we measure the ROI of Generative AI?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            In 2026, we measure ROI beyond just \"hours saved.\" We look at \u003cstrong\u003eTotal Cost of Ownership (TCO)\u003c\/strong\u003e vs. \u003cstrong\u003eValue Realized\u003c\/strong\u003e, including metrics like \"Time-to-Insight,\" \"Customer Satisfaction (CSAT) uplift,\" and the reduction in operational error rates through automated validation.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eDoes this course require technical programming knowledge?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            No. This is a \u003cstrong\u003eStrategic \u0026amp; Operational\u003c\/strong\u003e course. While we explain the architecture of LLMs and RAG so you can talk to your engineering teams, the focus is on business value, organizational design, risk management, and ROI.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757040488773,"sku":null,"price":399.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/aiBusTrans_8117845d-cdb8-47db-b6ce-1fdfc71c97b1.webp?v=1770128502"},{"product_id":"generative-ai-introduction-and-overview","title":"Generative AI Introduction and Overview Training","description":"\u003cdiv class=\"dt-product-description-v7\"\u003e\n\u003ch2 class=\"dt-heading-xl\"\u003eGenerative AI Introduction and Overview Training\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eGenerative AI Introduction and Overview is an online training course designed to help learners understand how modern AI systems work and how they are applied in real business and technical environments. This course focuses on building clear understanding of large language models, prompt engineering, multimodal AI and practical AI workflows. \u003cbr\u003e\u003cbr\u003eBased on the provided course content, the training covers key concepts such as transformer models, prompt strategies, retrieval augmented generation, multimodal AI and responsible AI. It is designed for professionals who want to move beyond basic awareness and gain a structured understanding of how generative AI can be applied in practice. \u003cbr\u003e\u003cbr\u003ePlease note that this product provides training only. No coding experience is required.\u003c\/div\u003e\n\u003cdiv class=\"dt-container-v7\"\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv\u003e\n\u003ch3 class=\"dt-heading-card\"\u003e\n\u003cbr\u003eWho is this training for\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eBusiness leaders and managers exploring AI-driven efficiency and innovation\u003c\/li\u003e\n\u003cli\u003eTechnical professionals looking to understand LLMs and AI systems\u003c\/li\u003e\n\u003cli\u003eContent creators and marketers using AI for text, image and media generation\u003c\/li\u003e\n\u003cli\u003eConsultants working with AI strategy, risk and implementation\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eAI Strategy Consultant\u003c\/li\u003e\n\u003cli\u003eAI Implementation Manager\u003c\/li\u003e\n\u003cli\u003ePrompt Engineer\u003c\/li\u003e\n\u003cli\u003eDigital Transformation Lead\u003c\/li\u003e\n\u003cli\u003eAI Product Owner\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eCore Learning Topics\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eThe Mechanics of Generative AI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eUnderstand how transformer models and large language models work, including how AI predicts and generates content based on patterns in data.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003ePrompt Engineering and Context \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLearn how to structure prompts, manage context and improve output quality using different prompting techniques.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eRAG and Fine Tuning Concepts \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eExplore how AI systems can be adapted using external data sources or customization techniques to improve relevance and accuracy.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eMultimodal AI Applications \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLearn how AI can work across text, images, audio and video and how these capabilities are used in modern applications.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eResponsible AI and Governance \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eUnderstand ethical considerations, risk management and governance principles for using AI in business environments.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eCareer Opportunities\u003c\/h3\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eThis course supports professionals who want to build a strong foundation in generative AI without needing a technical background. It is especially useful for roles that require understanding AI capabilities, use cases and strategic implementation. \u003cbr\u003e\u003cbr\u003eThe training is also relevant for organizations that want to build a shared understanding of AI across business and technical teams. \u003cbr\u003e\u003cbr\u003eFor organizations looking to train multiple employees, visit \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eteam training options\u003c\/a\u003e.\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWhat is generative AI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eGenerative AI creates new content such as text, images or code based on patterns learned from data.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\" open=\"\"\u003e\n\u003csummary\u003eDo I need coding experience \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eNo. This course focuses on understanding and applying AI concepts without requiring programming.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\" open=\"\"\u003e\n\u003csummary\u003eWhat is prompt engineering \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003ePrompt engineering is the process of structuring inputs to guide AI models toward better outputs.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWhat is RAG in AI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eRAG allows AI models to use external data sources to improve accuracy and reduce incorrect outputs.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\" open=\"\"\u003e\n\u003csummary\u003eWho should take this course \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThis course is suitable for business professionals, technical users and anyone exploring generative AI applications.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757041439045,"sku":null,"price":299.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/aiIntro_819769f7-4ab7-4432-ae91-e38bc30e4da8.webp?v=1770129605"},{"product_id":"image-generation-with-ai","title":"Image Generation with AI 2025 Updated","description":"\u003cp\u003e\u003cstrong\u003eCreate Visual Content with the Power of Artificial Intelligence\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eThe Image Generation with AI Learning Kit is designed for professionals who want to understand how AI-generated images are created and how they are used in real-world scenarios. Powered by Skillsoft, this Learning Kit focuses on the principles, tools and practical applications behind modern AI image generation.\u003c\/p\u003e\n\u003cp\u003eYou learn how generative AI models create images, how prompts influence visual output and how AI-generated visuals are applied in marketing, design, content creation and product development. This Learning Kit is practical, accessible and focused on real use cases rather than deep technical implementation.\u003c\/p\u003e\n\u003ch3\u003eKey Advantages of This Learning Kit\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAccessible:\u003c\/strong\u003e no design or programming background required.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePractical:\u003c\/strong\u003e real-world examples of AI-generated images and workflows.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRelevant:\u003c\/strong\u003e aligned with current AI image generation trends.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFlexible:\u003c\/strong\u003e 365 days access, learn at your own pace on any device.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSupported:\u003c\/strong\u003e 24\/7 live tutor support when you need guidance.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eWhat You Will Learn\u003c\/h3\u003e\n\u003cp\u003eThis Learning Kit builds practical understanding of AI-driven image creation:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eHow AI image generation works at a conceptual level\u003c\/li\u003e\n\u003cli\u003eThe role of prompts in shaping visual output\u003c\/li\u003e\n\u003cli\u003eCommon tools and platforms for AI image generation\u003c\/li\u003e\n\u003cli\u003eUse cases for marketing, design and content creation\u003c\/li\u003e\n\u003cli\u003eEthical, legal and responsible use of AI-generated images\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eWho This Learning Kit Is For\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMarketing and Content Professionals:\u003c\/strong\u003e creating visual assets faster.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eDesigners and Creatives:\u003c\/strong\u003e exploring AI-assisted visual creation.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eBusiness Professionals:\u003c\/strong\u003e using AI images in presentations and products.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eCareer Switchers:\u003c\/strong\u003e building AI literacy for creative and digital roles.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eImportant:\u003c\/strong\u003e This Learning Kit focuses on understanding and applying AI image generation tools, not on building AI models from scratch.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eCreate smarter visuals.\u003c\/strong\u003e Start the Image Generation with AI Learning Kit and learn how to use AI to enhance creativity and productivity.\u003c\/p\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757045272901,"sku":null,"price":299.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/image-generation-with-ai-learning-kit.png?v=1770130088"},{"product_id":"leveraging-generative-ai-apis","title":"Leveraging Generative AI APIs","description":"\u003ch2 class=\"dt-heading-xl\"\u003eFrom Prompting to Programming: Leveraging Generative AI APIs (2026 Updated)\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eThe true power of Generative AI is not found in a chat interface, but in the \u003cstrong\u003eAPI layer\u003c\/strong\u003e. In 2026, the competitive edge for developers and enterprises lies in the ability to programmatically orchestrate Large Language Models (LLMs) into custom workflows. This elite training path provides the technical authority to integrate industry-leading models—including \u003cstrong\u003eOpenAI (GPT-4o)\u003c\/strong\u003e, \u003cstrong\u003eAnthropic (Claude 3.5), and Google (Gemini 1.5 Pro), \u003c\/strong\u003edirectly into your applications. You will move beyond simple API calls to master the high-stakes engineering of \u003cstrong\u003eFunction Calling, JSON Mode, and State Management\u003c\/strong\u003e. Whether you are building autonomous support agents or real-time data synthesis engines, this course provides the mastery required to build production-grade AI systems that are reliable, secure, and cost-optimized.\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-glass-panel-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eWho is this for?\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003e\n\u003cstrong\u003eSoftware Developers\u003c\/strong\u003e aiming to integrate \"intelligence\" features into existing web or mobile apps.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAI Engineers\u003c\/strong\u003e looking to master the technical nuances of multimodal APIs and token management.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSolutions Architects\u003c\/strong\u003e designing the infrastructure for high-throughput AI inference at scale.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eData Scientists\u003c\/strong\u003e transitioning from experimental notebooks to production-ready API services.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-glass-panel-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eAI Software Engineer\u003c\/li\u003e\n\u003cli\u003eLLM Integration Specialist\u003c\/li\u003e\n\u003cli\u003eFull-Stack AI Developer\u003c\/li\u003e\n\u003cli\u003eCognitive Systems Architect\u003c\/li\u003e\n\u003cli\u003eMachine Learning Operations (MLOps) Engineer\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eCourse Curriculum\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eAPI Fundamentals: Authentication \u0026amp; Tokenomics \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eMaster the mechanics of AI communication. Learn to manage API keys securely, understand the difference between \u003cstrong\u003eInput vs. Output tokens\u003c\/strong\u003e, and implement efficient rate-limiting strategies. We explore the economics of different models, teaching you how to select the right \"brain\" for the task based on latency, cost, and context window requirements.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eStructured Outputs: JSON Mode \u0026amp; Function Calling \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eAI is only useful if it talks back in a language your code understands. Master \u003cstrong\u003eJSON Mode\u003c\/strong\u003e and \u003cstrong\u003ePydantic-based schemas\u003c\/strong\u003e to ensure consistent data structures. Learn \u003cstrong\u003eFunction Calling\u003c\/strong\u003e (Tool Use), enabling your model to interact with external databases, browse the web, or execute code to solve complex user requests.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eManaging State: Context Windows \u0026amp; Threading \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLLMs are stateless by nature—learn to give them a \"memory.\" Master the management of chat histories, summarization techniques for long-running conversations, and the utilization of \u003cstrong\u003eVector Databases\u003c\/strong\u003e for Retrieval-Augmented Generation (RAG). Learn to optimize context windows to maintain relevance without ballooning costs.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eMultimodal Integrations: Vision \u0026amp; Audio APIs \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eMove beyond text. Master the 2026 standard for \u003cstrong\u003eNative Multimodality\u003c\/strong\u003e. Learn to pass images to Vision models for analysis, integrate Text-to-Speech (TTS) and Speech-to-Text (STT) APIs for voice interfaces, and use Video Analysis APIs to extract semantic meaning from raw footage programmatically.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eMonitoring, Evaluation (Eval), \u0026amp; Fine-Tuning \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eEnsure production reliability. Learn to implement \u003cstrong\u003eEvals\u003c\/strong\u003e to measure model performance and regression. Master logging tools to track prompt-response pairs and identify where models fail. Finally, explore when to move from API-based prompting to \u003cstrong\u003eParameter-Efficient Fine-Tuning (PEFT)\u003c\/strong\u003e for hyper-specialized tasks.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-faq-item-v7\"\u003e\n\u003csummary\u003eWhich API should I start with: OpenAI, Claude, or Gemini?\u003c\/summary\u003e\n\u003cdiv class=\"dt-faq-answer\"\u003eOpenAI is currently the industry standard for general versatility and documentation. Anthropic (Claude) is preferred for complex reasoning and long-context documents. Google (Gemini) excels in massive context windows (up to 2M tokens) and native multimodality. This course teaches you a \u003cstrong\u003eModel-Agnostic\u003c\/strong\u003e approach so you can switch between them as needed.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-faq-item-v7\"\u003e\n\u003csummary\u003eIs it safe to put my company data into an LLM API?\u003c\/summary\u003e\n\u003cdiv class=\"dt-faq-answer\"\u003eEnterprise-grade API accounts (like OpenAI Enterprise or Azure OpenAI) generally provide data privacy guarantees where your data is *not* used to train the base models. This course covers \u003cstrong\u003eSecurity \u0026amp; Compliance\u003c\/strong\u003e, teaching you how to use data masking and private endpoints to protect sensitive information.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-faq-item-v7\"\u003e\n\u003csummary\u003eWhat is \"Function Calling\" and why is it important?\u003c\/summary\u003e\n\u003cdiv class=\"dt-faq-answer\"\u003eFunction Calling allows an LLM to act as a \"controller.\" It can recognize when a user wants to check a price, update a record, or send an email, and it outputs the necessary code\/parameters for your application to execute that action. This transforms the AI from a talker into a **doer**.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757048385861,"sku":null,"price":349.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/leveraging-generative-ai-apis-learning-kit.png?v=1770130992"},{"product_id":"mlops-machine-learning-operations","title":"MLOps (Machine Learning Operations)","description":"\u003ch2 class=\"dt-heading-xl\"\u003eBridging the Gap: Master the Lifecycle of Production-Grade AI with MLOps\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003e\n    The \"MLOps (Machine Learning Operations)\" program is an elite technical track designed to solve the \"last mile\" problem in artificial intelligence. While many can build a model, few can deploy, monitor, and scale one reliably in a production environment. Powered by Skillsoft, this course provides the engineering framework necessary to transition from experimental notebooks to automated, self-healing pipelines. You will master the 2026 standards for CI\/CD\/CT (Continuous Integration, Deployment, and Training), data versioning, and model observability. By bridging the gap between Data Science and DevOps, this training ensures your models remain accurate, compliant, and performant long after the initial deployment.\n\u003c\/div\u003e\n\n\u003cdiv class=\"dt-grid-v7\"\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eWho is this for?\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003eData Scientists:\u003c\/strong\u003e Looking to move beyond experimental modeling to understand how their code lives in production.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eDevOps Engineers:\u003c\/strong\u003e Professionals aiming to specialize in the unique requirements of machine learning infrastructure and hardware acceleration.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eMachine Learning Engineers:\u003c\/strong\u003e Individuals focused on building robust, automated pipelines for model retraining and deployment.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eSoftware Architects:\u003c\/strong\u003e Technical leads designing the structural foundation for AI-integrated enterprise applications.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eIT Operations Managers:\u003c\/strong\u003e Leaders tasked with managing the cost, compliance, and reliability of organizational AI assets.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003eMLOps Engineer:\u003c\/strong\u003e Automating the end-to-end lifecycle of machine learning models and ensuring pipeline stability.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eAI Infrastructure Architect:\u003c\/strong\u003e Designing scalable cloud and hybrid environments for model training and inference.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eLLMOps Specialist:\u003c\/strong\u003e Managing the unique challenges of Large Language Models, including fine-tuning pipelines and RAG orchestration.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eModel Reliability Engineer:\u003c\/strong\u003e Monitoring model health, detecting drift, and implementing automated retraining triggers.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eData Engineer (ML Focus):\u003c\/strong\u003e Building the feature stores and data pipelines that feed high-performance models.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n\u003c\/div\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eCourse Curriculum\u003c\/h3\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 1: The MLOps Framework \u0026amp; Principles \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Understand why ML is different from traditional software. Explore the \"Hidden Technical Debt\" in ML systems. Learn the core pillars of MLOps: reproducibility, accountability, and collaborative development. This module introduces the maturity levels of MLOps, from manual processes to fully automated CI\/CD pipelines.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 2: Data \u0026amp; Model Versioning (DVC \u0026amp; MLflow) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        In MLOps, code versioning is not enough. Master tools like DVC (Data Version Control) to track datasets and MLflow for experiment tracking and model registries. Learn to manage the \"Lineage\" of a model, ensuring you know exactly which data and which code produced every production asset.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 3: Automated Pipelines \u0026amp; CI\/CD\/CT \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Build the automated engine. Master the implementation of \u003cstrong\u003eContinuous Training (CT)\u003c\/strong\u003e, where pipelines automatically retrain models when new data arrives or performance drops. Learn to use Kubeflow, TFX (TensorFlow Extended), or GitHub Actions to orchestrate complex multi-step ML workflows.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 4: Model Deployment \u0026amp; Serving Strategies \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Get models into the hands of users. Explore deployment patterns including Canary releases, Blue\/Green deployments, and A\/B testing. Learn the nuances of high-performance serving using Seldon Core, NVIDIA Triton, or Kubernetes-based inference services (KServe).\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 5: Monitoring, Drift Detection \u0026amp; LLMOps \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Ensure your models don't \"go rogue.\" Learn to detect \u003cstrong\u003eConcept Drift\u003c\/strong\u003e and \u003cstrong\u003eData Drift\u003c\/strong\u003e using statistical checks. New for 2026, this module includes LLMOps essentials: monitoring LLM hallucinations, managing vector database health, and auditing generative outputs for safety and compliance.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\n\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eHow does MLOps differ from standard DevOps?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            DevOps focuses on code and infrastructure. MLOps adds a third dimension: \u003cstrong\u003eData\u003c\/strong\u003e. In ML, even if the code doesn't change, the model's performance can degrade because the real-world data it processes changes (Drift). MLOps introduces Continuous Training (CT) to handle this specific challenge.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eDo I need to be a Ph.D. in Mathematics for this course?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            No. This is an engineering-first course. While a basic understanding of how ML models work is required, the focus is on the tooling, automation, and infrastructure (Kubernetes, Docker, CI\/CD tools) rather than deep mathematical theory.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eIs this course cloud-specific?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            We focus on \"Cloud-Agnostic\" principles using open-source tools like MLflow, Kubernetes, and DVC. However, we do provide specific implementation guides for the \"Big Three\" (AWS SageMaker, Azure ML, and Google Vertex AI) so you can apply these skills in any enterprise environment.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eWhat is LLMOps and is it included?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            LLMOps is a subset of MLOps tailored specifically for Large Language Models. It includes managing prompt versions, RAG (Retrieval-Augmented Generation) pipelines, and cost\/latency optimization for LLM APIs. This is a core part of the 2026 update for this course.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757052416325,"sku":null,"price":349.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/MLops_8c8d1262-a59f-4180-8991-ad3f19123dab.webp?v=1770132033"},{"product_id":"natural-language-processing-nlp","title":"Natural Language Processing (NLP)","description":"\u003ch2 class=\"dt-heading-xl\"\u003eMaster the Language of AI: From Tokenization to Large Language Model Orchestration\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003e\n    The \"Natural Language Processing (NLP)\" program is an advanced technical track designed to turn data scientists and developers into experts in computational linguistics. Powered by Skillsoft, this 2026-updated curriculum bridges the gap between traditional statistical NLP and the modern era of Generative Pre-trained Transformers (GPT). You will explore the evolution of language processing, moving from basic text cleaning and sentiment analysis to building sophisticated RAG (Retrieval-Augmented Generation) systems and fine-tuning open-source LLMs. By mastering vector embeddings, attention mechanisms, and semantic search, you will gain the skills necessary to build applications that don't just \"read\" text, but truly understand context, nuance, and intent at an enterprise scale.\n\u003c\/div\u003e\n\n\u003cdiv class=\"dt-grid-v7\"\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eWho is this for?\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003eData Scientists:\u003c\/strong\u003e Looking to specialize in unstructured data and master the latest Transformer-based architectures.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eAI Engineers:\u003c\/strong\u003e Professionals aiming to build and deploy custom LLM-powered agents and semantic search engines.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eMachine Learning Engineers:\u003c\/strong\u003e Individuals focused on optimizing model performance through fine-tuning and quantization.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eSoftware Developers:\u003c\/strong\u003e Engineers looking to integrate advanced NLP features like translation, summarization, and named entity recognition (NER).\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eResearch Analysts:\u003c\/strong\u003e Academics and industry researchers exploring the intersection of human language and probabilistic modeling.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003eNLP Engineer:\u003c\/strong\u003e Designing and implementing models for text classification, language translation, and dialogue systems.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eLLM Architect:\u003c\/strong\u003e Blueprinting enterprise-scale systems that combine vector databases with generative models.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eComputational Linguist:\u003c\/strong\u003e Analyzing the structural and semantic properties of language to improve model accuracy and fairness.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eAI Product Manager:\u003c\/strong\u003e Overseeing the development of language-centric products like chatbots, virtual assistants, and search tools.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eMachine Learning Researcher:\u003c\/strong\u003e Pushing the boundaries of what is possible in speech-to-text and natural language understanding.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n\u003c\/div\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eCourse Curriculum\u003c\/h3\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 1: Foundations of Text Processing \u0026amp; Vectorization \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Start with the building blocks. Learn about tokenization, stop-word removal, and lemmatization. Master the transition from traditional TF-IDF and Bag-of-Words models to modern Word Embeddings (Word2Vec, GloVe) and understanding the multi-dimensional vector space where language lives.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 2: The Transformer Revolution \u0026amp; Attention Mechanisms \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Deep dive into the architecture that changed everything. Understand Self-Attention, Multi-Head Attention, and the Encoder-Decoder framework. Explore the BERT (Bidirectional Encoder Representations from Transformers) model family and how it revolutionized context-aware understanding in NLP.\n        \n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 3: Large Language Models (LLMs) \u0026amp; Fine-Tuning \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Move into the generative era. Learn to work with the GPT family and open-source alternatives like Llama 3 and Mistral. Master Parameter-Efficient Fine-Tuning (PEFT) techniques like LoRA and QLoRA to adapt massive models to specific domain tasks without needing a supercomputer.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 4: Semantic Search \u0026amp; RAG Architectures \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Build the bridge between LLMs and private data. Learn to implement Retrieval-Augmented Generation (RAG) using vector databases (Pinecone, Weaviate). Master the pipeline of document chunking, embedding generation, and similarity search to build highly accurate, grounded AI systems.\n        \n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 5: Evaluation, Ethics \u0026amp; Bias in NLP \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Measure success and ensure safety. Learn to evaluate models using metrics like BLEU, ROUGE, and METEOR. Critically analyze the ethical implications of NLP, including data poisoning, algorithmic bias, and the environmental impact of training large-scale models.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eWhat is the difference between NLU and NLG?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            Natural Language Understanding (NLU) focuses on the machine's ability to comprehend the meaning and intent behind text (classification, NER). Natural Language Generation (NLG) focuses on the machine's ability to produce human-like text based on structured data or prompts. Modern LLMs excel at both.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eDo I need high-end GPUs to participate in this course?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            While fine-tuning massive models requires significant compute, our Skillsoft-powered labs provide cloud-based environments with the necessary GPU power. You will also learn techniques to run smaller, optimized models on standard hardware.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eIs this course focused more on theory or practical application?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            We maintain a strict 40\/60 balance. You need the mathematical theory to understand how weights and attention work, but 60% of the course is hands-on coding in Python, using libraries like Hugging Face Transformers, PyTorch, and LangChain.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eHow does NLP differ from standard Machine Learning?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            Standard ML often deals with structured, numerical data. NLP deals with \"unstructured\" sequential data. The primary challenge in NLP is converting the ambiguity and complexity of human language into a numerical format (vectors) that a machine can process.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757059592517,"sku":null,"price":329.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/nlp_48dfd4a9-f158-4902-8adb-faf52d4e1289.webp?v=1748028999"},{"product_id":"natural-language-processing-and-llms","title":"Natural Language Processing and LLMs","description":"\u003ch2 class=\"dt-heading-xl\"\u003eMaster the Era of Generative AI with Natural Language Processing \u0026amp; LLMs\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003e\n    The explosion of Generative AI has transformed the technological landscape, placing Natural Language Processing (NLP) at the heart of modern innovation. This specialized course offers an elite deep dive into the architectures that power tools like ChatGPT, Claude, and Gemini. You will progress from the foundational mechanics of linguistics and tokenization to the sophisticated implementation of Transformer models and Large Language Models (LLMs). This curriculum is designed for those who want to move beyond simple prompt engineering into the realm of building, fine-tuning, and deploying intelligent language systems. By mastering RAG (Retrieval-Augmented Generation), vector databases, and model optimization, you will position yourself at the absolute forefront of the AI revolution, ready to solve complex real-world problems with machine intelligence.\n\u003c\/div\u003e\n\n\u003cdiv class=\"dt-grid-v7\"\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eWho is this for?\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003eData Scientists looking to specialize in advanced Deep Learning and Transformers.\u003c\/li\u003e\n            \u003cli\u003eSoftware Engineers aiming to integrate LLM capabilities into enterprise applications.\u003c\/li\u003e\n            \u003cli\u003eAI Researchers focused on the latest developments in Generative Pre-trained Transformers.\u003c\/li\u003e\n            \u003cli\u003eTechnical Leads responsible for implementing AI-driven automation and chatbots.\u003c\/li\u003e\n            \u003cli\u003eMachine Learning Engineers wanting to master fine-tuning and model quantization techniques.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003eNLP Engineer\u003c\/li\u003e\n            \u003cli\u003eAI Solutions Architect\u003c\/li\u003e\n            \u003cli\u003eMachine Learning Specialist\u003c\/li\u003e\n            \u003cli\u003eLLM Developer\u003c\/li\u003e\n            \u003cli\u003eGenerative AI Researcher\u003c\/li\u003e\n            \u003cli\u003eComputational Linguist\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n\u003c\/div\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eCourse Curriculum\u003c\/h3\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 1: Foundations of NLP and Text Processing \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Before mastering LLMs, you must understand the language of machines. This module covers essential text preprocessing techniques, including tokenization, lemmatization, and stop-word removal. You will explore traditional word embeddings like Word2Vec and GloVe, and understand how numerical representations of language form the basis for all modern AI models.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 2: The Transformer Revolution and Attention Mechanisms \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Explore the architecture that changed everything. This module provides a technical breakdown of the \"Attention is All You Need\" paper, covering Self-Attention, Multi-Head Attention, and Encoder-Decoder structures. You will understand why Transformers outperformed previous RNN and LSTM models to become the industry standard.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 3: Large Language Models (LLMs) and Pre-training \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Dive into the lifecycle of an LLM. Learn about the massive datasets and self-supervised learning techniques used during pre-training. This module compares major model families (GPT, Llama, BERT) and discusses the scaling laws that govern model performance, parameters, and computational requirements.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 4: Fine-Tuning, RAG, and Advanced Implementation \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Learn how to make a general model a domain expert. This module covers Supervised Fine-Tuning (SFT), Parameter-Efficient Fine-Tuning (PEFT\/LoRA), and Retrieval-Augmented Generation (RAG). You will explore vector databases like Pinecone or Weaviate to provide models with long-term memory and specific organizational knowledge.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 5: Ethical AI and Deployment Strategies \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Deploying AI requires more than just code. Learn about model quantization to reduce hardware costs, API integration, and monitoring for \"hallucinations.\" This module also addresses the critical ethical considerations of AI, including bias mitigation, safety alignment (RLHF), and data privacy in an LLM-driven world.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eDo I need to be an expert in Python to follow this course?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            An intermediate knowledge of Python is highly recommended, as the course involves working with libraries such as PyTorch, Hugging Face Transformers, and LangChain. Familiarity with basic calculus and linear algebra will also help in understanding model architectures.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eWill I learn how to build my own ChatGPT-like application?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            Yes. A core component of this course is practical application. You will learn how to use frameworks like LangChain to build applications that can \"chat\" with your own documents, utilize external tools, and maintain conversational context.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eWhat is the difference between Prompt Engineering and the content of this course?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            Prompt Engineering is the art of writing better inputs. This course is about the engineering behind the model—how to fine-tune weights, manage vector embeddings, and architect the systems that make those prompts effective and reliable at scale.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eAre there specific hardware requirements for the labs?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            While local GPUs are beneficial, the course labs are designed to run on cloud-based environments like Google Colab or Kaggle. We will also discuss how to use API-based models (like OpenAI or Anthropic) which do not require any specialized local hardware.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757060739397,"sku":null,"price":349.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/nlpllm_b9fc1c30-3956-45db-96c4-b571d37b971c.webp?v=1770134357"},{"product_id":"pair-programming-with-generative-ai-tools","title":"Pair Programming with Generative AI Tools","description":"\u003cdiv class=\"dt-product-description-v7\"\u003e\n  \u003ch2 class=\"dt-heading-xl\"\u003ePair Programming with Generative AI Tools Training\u003c\/h2\u003e\n\n  \u003cdiv class=\"dt-body-premium\"\u003e\n    Pair Programming with Generative AI Tools is designed to help developers build practical skills in modern AI-assisted software development. This training focuses on how to work more effectively with generative AI during coding, debugging, refactoring, testing and secure development workflows.\n    \u003cbr\u003e\u003cbr\u003e\n    Based on the provided course content, the training supports professionals who want to use AI tools as collaborative development partners while maintaining code quality, architectural control and security awareness. It is a strong fit for engineers, junior developers, technical leads, DevOps professionals and QA specialists who want a more efficient and structured coding workflow.\n  \u003c\/div\u003e\n\n  \u003cdiv class=\"dt-container-v7\"\u003e\n    \u003cdiv class=\"dt-grid-v7\"\u003e\n      \u003cdiv\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eWho is this training for\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n          \u003cli\u003eSoftware engineers improving speed and consistency with AI-assisted coding\u003c\/li\u003e\n          \u003cli\u003eJunior developers who want more guidance during coding and debugging\u003c\/li\u003e\n          \u003cli\u003eTechnical leads standardizing AI-supported development workflows across teams\u003c\/li\u003e\n          \u003cli\u003eDevOps engineers automating scripts, infrastructure tasks and troubleshooting\u003c\/li\u003e\n          \u003cli\u003eQA engineers using AI to support test generation and code review\u003c\/li\u003e\n        \u003c\/ul\u003e\n      \u003c\/div\u003e\n\n      \u003cdiv\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n          \u003cli\u003eAI-Augmented Developer\u003c\/li\u003e\n          \u003cli\u003eSenior Software Architect\u003c\/li\u003e\n          \u003cli\u003eFull-Stack Agentic Engineer\u003c\/li\u003e\n          \u003cli\u003eLead Code Reviewer\u003c\/li\u003e\n          \u003cli\u003eAI Implementation Specialist\u003c\/li\u003e\n        \u003c\/ul\u003e\n      \u003c\/div\u003e\n    \u003c\/div\u003e\n  \u003c\/div\u003e\n\n  \u003ch3 class=\"dt-heading-section\"\u003eCourse Modules\u003c\/h3\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eThe AI Pair Programming Paradigm \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Learn how modern AI pair programming works in practice, including the role of the developer as decision-maker and the AI as a support layer for generation, explanation and iteration.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eContext Management and Multi-File Reasoning \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Build practical skills in giving AI tools the right project context so they can support larger codebases, multiple files and more consistent implementation decisions.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eAdvanced Debugging and the Edit-Test Loop \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Learn how to use AI during debugging, test creation and iterative fixing so you can work through bugs with more structure and less repetitive manual effort.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eAI-Driven Refactoring and System Design \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Understand how AI can support larger code changes, refactors and architecture-level thinking while keeping human oversight central to quality and design choices.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eSecurity Ethics and Responsible AI Coding \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Build awareness of secure and responsible AI-assisted coding, including how to review generated code, think about privacy and avoid blindly accepting risky suggestions.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003ch3 class=\"dt-heading-section\"\u003eCareer Opportunities\u003c\/h3\u003e\n\n  \u003cdiv class=\"dt-body-premium\"\u003e\n    This training supports developers and technical teams who want to improve productivity, reduce repetitive work and build stronger AI-assisted engineering workflows. It is especially useful for professionals who want to combine software development skills with modern AI tooling in a more practical and responsible way.\n    \u003cbr\u003e\u003cbr\u003e\n    The included labs also make this training relevant for teams that want to test, standardize and scale AI-supported coding practices across engineering environments.\n    \u003cbr\u003e\u003cbr\u003e\n    For organizations looking to train multiple employees, visit \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eteam training options\u003c\/a\u003e.\n  \u003c\/div\u003e\n\n  \u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\n  \u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eWhat are the prerequisites for this AI pair programming course \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        A basic understanding of at least one programming language and familiarity with an IDE are recommended. No prior AI tool experience is required based on the provided course content.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eCan AI coding tools help with multi-file development \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        Yes. Modern AI coding tools can work with broader project context and support reasoning across multiple files when used with the right workflow and context setup.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eCan these tools be used in secure company environments \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        Yes, but privacy and access settings matter. Teams should use enterprise controls and responsible data handling practices when adopting AI coding tools.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eDoes this course include practical labs \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        Yes. Based on the provided product content, the course includes hands-on labs for real-world AI-assisted development practice.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eWhich tools are relevant to this training \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        Based on the provided content, the training covers AI-assisted development workflows built around tools such as GitHub Copilot, Cursor and Claude Code.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n  \u003c\/div\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757064900933,"sku":null,"price":389.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/AiProgram_5b280ff6-1b4a-4284-b803-96094ea2b35a.webp?v=1770135242"},{"product_id":"practical-chatgpt-from-use-cases-to-prompt-engineering-ethical-implications","title":"Practical ChatGPT Learning Kit, Use Cases, Prompt Engineering, Ethical Implications","description":"\u003ch2 class=\"dt-heading-xl\"\u003eMaster the AI Revolution: A Hands-On Journey Through ChatGPT, Prompt Engineering, and Professional AI Integration\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003e\n    The \"Practical ChatGPT Learning Kit\" is a comprehensive technical roadmap designed to transform how you work, think, and create in the age of Generative AI. Powered by Skillsoft, this course strips away the hype to focus on the tangible, high-value applications of Large Language Models (LLMs) in the modern workplace. You will move beyond simple queries to master the \"AI Co-pilot\" mindset, learning to architect complex prompt sequences that deliver consistent, enterprise-ready results. From automating data-heavy business processes to navigating the critical ethical landscapes of data privacy and algorithmic bias, this kit provides the practical framework required to lead AI initiatives with confidence, precision, and a deep understanding of the future of human-AI collaboration.\n\u003c\/div\u003e\n\n\u003cdiv class=\"dt-grid-v7\"\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eWho is this for?\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003eBusiness Professionals:\u003c\/strong\u003e Looking to automate administrative overhead, draft complex communications, and summarize high volumes of data.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eContent Creators:\u003c\/strong\u003e Strategists aiming to use AI for high-fidelity brainstorming, SEO optimization, and multi-format content scaling.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eEducators \u0026amp; Trainers:\u003c\/strong\u003e Professionals wanting to build personalized learning paths and interactive training materials using AI agents.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eProject Managers:\u003c\/strong\u003e Leads seeking to streamline roadmap planning, risk assessment, and stakeholder reporting via structured prompting.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eKnowledge Workers:\u003c\/strong\u003e Anyone looking to future-proof their career by becoming an \"AI-augmented\" specialist in their field.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003eAI Implementation Lead:\u003c\/strong\u003e Guiding teams on the practical integration of ChatGPT into existing daily workflows.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003ePrompt Specialist:\u003c\/strong\u003e Designing and maintaining organizational \"prompt libraries\" for consistent quality control.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eDigital Content Strategist:\u003c\/strong\u003e Orchestrating AI-driven campaigns that maintain brand voice and high engagement.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eAI Ethics Coordinator:\u003c\/strong\u003e Ensuring that the use of Generative AI meets corporate compliance and data privacy standards.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eOperational Excellence Manager:\u003c\/strong\u003e Using AI to identify and eliminate bottlenecks in business and technical processes.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n\u003c\/div\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eCourse Curriculum\u003c\/h3\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 1: The ChatGPT Architecture \u0026amp; Core Capabilities \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Understand the \"Engine\" under the hood. Learn how GPT (Generative Pre-trained Transformer) models work, the concept of tokenization, and why the model's \"context window\" is critical to your success. Explore the differences between free and plus tiers, including the use of specialized GPTs and multimodal features (Voice, Image, Vision).\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 2: Advanced Prompt Engineering Frameworks \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Move beyond the \"Ask and Hope\" method. Master professional frameworks like the \u003cstrong\u003eCO-STAR\u003c\/strong\u003e method (Context, Objective, Style, Tone, Audience, Response). Learn advanced techniques such as \"Few-Shot\" prompting, \"Chain-of-Thought\" reasoning, and \"Role-Playing\" to force the model into high-precision technical outputs.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 3: Real-World Business Use Cases \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Put AI to work. This module explores specific applications: automating meeting summaries, generating complex Excel formulas from natural language, drafting legal and technical documents, and using ChatGPT for rapid market research. Learn to use AI for \"Oppositional Thinking\" to stress-test your business strategies.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 4: Managing Hallucinations \u0026amp; Information Accuracy \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Learn to trust but verify. Understand why AI \"hallucinates\" and how to implement \"Grounding\" techniques to minimize errors. Master the art of \"Source Verification\" and \"Iterative Refinement\" to ensure that the outputs you use for professional tasks are factually sound and logically consistent.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 5: Ethical Implications \u0026amp; Data Privacy \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Navigate the \"Dark Side\" of AI. This critical module covers the ethical implications of Generative AI, including algorithmic bias, the environmental impact of large models, and intellectual property concerns. Learn the \"Golden Rules\" of data privacy: what you should never share with a public AI and how to use enterprise-grade privacy settings.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eWill ChatGPT replace my job?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            AI likely won't replace your job, but a professional who knows how to use AI might. This course is designed to make you that professional by teaching you how to use ChatGPT as an \"exoskeleton for the mind,\" increasing your output quality and speed.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eIs it safe to put company data into ChatGPT?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            By default, data sent to public versions of ChatGPT can be used to train future models. This course teaches you how to navigate privacy settings, use \"Temporary Chats,\" and understand the benefits of \"ChatGPT Enterprise\" or \"Team\" accounts to keep your data confidential.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eDo I need to be a \"techie\" to learn Prompt Engineering?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            No. Prompt Engineering is more about clear communication, logic, and structured thinking than it is about coding. If you can explain a task to a colleague, you can learn to engineer a prompt. We provide the templates to bridge that gap.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eDoes this course cover other AI tools like Midjourney or Claude?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            While ChatGPT is our primary focus, the \"Prompt Engineering\" principles you learn here are universal. You will be able to apply 90% of these skills directly to other models like Anthropic's Claude, Google's Gemini, or image-generation tools like Midjourney.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757067227461,"sku":null,"price":329.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/gpt_edfd88b8-c9db-43bc-859f-e13033e1914e.webp?v=1748029019"},{"product_id":"prompt-engineering-for-ethical-hacking","title":"Prompt Engineering for Ethical Hacking Learning Kit","description":"\u003cdiv class=\"dt-product-description-v7\"\u003e\n\u003ch2 class=\"dt-heading-xl\"\u003ePrompt Engineering for Ethical Hacking Learning Kit\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003ePrompt Engineering for Ethical Hacking is designed to help security professionals build practical skills in using generative AI more effectively within legitimate security workflows. This training focuses on how structured prompting can support security analysis, vulnerability review, reporting, triage and defensive testing in modern environments. \u003cbr\u003e\u003cbr\u003eBased on the provided course content, the Learning Kit supports professionals who want to combine ethical hacking knowledge with AI-assisted workflows in a more controlled and responsible way. It is a strong fit for penetration testers, security analysts, red teamers, researchers and technical professionals exploring the security impact of large language models. \u003cbr\u003e\u003cbr\u003eThis product provides training only and does not include a certification exam voucher.\u003c\/div\u003e\n\u003cdiv class=\"dt-container-v7\"\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eWho is this training for\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003ePenetration testers using AI to improve reconnaissance, analysis and reporting workflows\u003c\/li\u003e\n\u003cli\u003eSecurity analysts applying LLMs to triage, log review and technical investigation\u003c\/li\u003e\n\u003cli\u003eRed team professionals exploring AI-assisted social engineering simulations and research\u003c\/li\u003e\n\u003cli\u003eBug bounty hunters and researchers looking at AI-assisted discovery and analysis workflows\u003c\/li\u003e\n\u003cli\u003eSecurity teams building stronger understanding of LLM risk and prompt injection issues\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eAI-Augmented Pentester\u003c\/li\u003e\n\u003cli\u003eSecurity Automation Engineer\u003c\/li\u003e\n\u003cli\u003eThreat Hunter\u003c\/li\u003e\n\u003cli\u003eSecurity Researcher\u003c\/li\u003e\n\u003cli\u003eAdversarial AI Specialist\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eCourse Modules\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\" open=\"\"\u003e\n\u003csummary\u003eAI-Powered Reconnaissance and OSINT \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLearn how prompt engineering can support information gathering, summarization and structured analysis during legitimate security research and reconnaissance workflows.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eAutomated Vulnerability Analysis and Scanning \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eBuild practical skills in using AI to interpret scan outputs, organize findings, support prioritization and improve the speed of technical review in security assessments.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eAI-Assisted Exploit Analysis and Review \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eExplore how AI can support the analysis of security techniques, code understanding and controlled testing workflows while keeping human review central to safety and accuracy.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eSocial Engineering Simulation and Communication \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eUnderstand how generative AI can support authorized simulation planning, message drafting and scenario design for awareness and assessment purposes in professional security contexts.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eAdversarial Prompting and Securing AI Systems \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLearn the foundations of prompt injection, jailbreaking risks, defensive review and guardrail thinking so you can better assess and protect AI-enabled systems.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eCareer Opportunities\u003c\/h3\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eThis Learning Kit supports professionals who want to combine security knowledge with modern AI workflow skills. It is especially useful for teams and individuals working in ethical hacking, triage, security research and AI-related security review. \u003cbr\u003e\u003cbr\u003eThe included labs also make this training relevant for organizations that want to explore responsible AI use in security operations and strengthen awareness of LLM-specific risks. \u003cbr\u003e\u003cbr\u003eFor organizations looking to train multiple employees, visit \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eteam training options\u003c\/a\u003e.\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWhat is prompt engineering for ethical hacking \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eIt is the use of structured prompts to make AI systems more useful for legitimate security workflows such as analysis, summarization, triage, documentation and controlled testing.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWhat is prompt injection and why does it matter \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003ePrompt injection is a security issue where crafted input changes model behavior in unintended ways. It matters because it can lead to unsafe outputs, bypassed safeguards and broader AI system risk.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDo I need programming experience for this course \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eA basic understanding of scripting and networking is recommended based on the provided course content so you can properly review and validate AI output.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIs using AI in security work ethical \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eIt depends on scope, authorization and intent. This training is positioned for responsible and legitimate security use, with strong focus on review, boundaries and defensive value.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eAre practical labs included \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eYes. Based on the provided product content, this Learning Kit includes hands-on labs for applied security scenarios.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757070897477,"sku":null,"price":379.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/prompt_EH_03a7a033-4c16-4a8f-adf3-5bf3dc061bef.webp?v=1773173944"},{"product_id":"prompt-engineering-for-programmers-to-learn-python","title":"Prompt Engineering for Programmers to Learn Python","description":"\u003ch2 class=\"dt-heading-xl\"\u003eAccelerate Your Python Mastery: Using Generative AI to Transition Your Code to Pythonic Excellence\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003e\n    The \"Prompt Engineering for Programmers to Learn Python\" program is an elite technical track designed for developers who already speak one or more languages and want to fast-track their Python proficiency. Powered by Skillsoft, this course flips the traditional learning model by teaching you how to use Large Language Models (LLMs) as high-level architectural mentors. You will learn to construct precision prompts that translate your existing knowledge of Java, C#, or JavaScript into clean, idiomatic Python. By mastering the art of \"comparative prompting\" and AI-driven code refactoring, you will bypass the syntax hurdle and jump straight into mastering Python’s unique features—such as list comprehensions, decorators, and context managers—ensuring you build production-ready applications with the speed and precision of a senior Pythonista.\n\u003c\/div\u003e\n\n\u003cdiv class=\"dt-grid-v7\"\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eWho is this for?\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003eExperienced Developers:\u003c\/strong\u003e Pros in C++, Java, or JS who want to quickly add Python to their stack for data science, AI, or backend work.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eWeb Developers:\u003c\/strong\u003e Engineers looking to transition to frameworks like FastAPI or Django using AI as an architectural guide.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eData Professionals:\u003c\/strong\u003e Analysts or SQL experts who need to generate complex Python scripts for automation and data pipelines.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eTechnical Leads:\u003c\/strong\u003e Managers who want to standardize Pythonic best practices across a team using AI-generated style guides.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eSelf-Taught Coders:\u003c\/strong\u003e Programmers looking to fill conceptual gaps in their logic using AI-driven mentorship and real-time code explanation.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003ePython Backend Developer:\u003c\/strong\u003e Building scalable, maintainable server-side logic and RESTful APIs with modern Python.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eAI\/ML Engineer:\u003c\/strong\u003e Leveraging Python’s massive ecosystem of libraries to deploy and integrate generative models.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eAutomation Engineer:\u003c\/strong\u003e Designing sophisticated scripts to streamline cloud infrastructure and CI\/CD workflows.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eData Engineer:\u003c\/strong\u003e Crafting high-performance ETL pipelines and data transformation layers using specialized Python packages.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eFull-Stack Engineer:\u003c\/strong\u003e Bridging the gap between reactive frontends and robust, logic-heavy Python backends.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n\u003c\/div\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eCourse Curriculum\u003c\/h3\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 1: Comparative Prompting \u0026amp; Syntax Translation \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Leverage what you already know. Learn to use \"Translation Prompts\" to convert common patterns from your primary language (e.g., C-style for-loops) into idiomatic Python. Master prompts that explain the differences in memory management, typing (dynamic vs. static), and the importance of the Python \"Indentation Rule\" via AI-driven visual examples.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 2: Mastery of Pythonic Idioms \u0026amp; \"The Zen of Python\" \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Don't just write code; write *Pythonic* code. Learn to prompt for refactoring, where the AI takes functional but \"clunky\" code and transforms it using list comprehensions, generators, and the 'enumerate' function. Understand how to use AI to audit your code against PEP 8 standards and the principles of \"The Zen of Python.\"\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 3: AI-Driven Debugging \u0026amp; Error Interpretation \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Turn Tracebacks into learning opportunities. Learn to feed Python’s often cryptic error messages into an LLM to receive a step-by-step logic breakdown. Master prompts that ask for \"Remediation Plans\" to fix common pitfalls like Mutable Default Arguments or the differences between 'is' and '==' equality.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 4: Mastering Advanced Features with AI Mentorship \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Tackle the \"hard stuff\" with ease. Use specialized prompts to explain and generate examples of Decorators, Context Managers (the 'with' statement), and Asynchronous Programming (async\/await). Learn to ask for \"Boilerplate Scaffolding\" for complex class structures and dunder methods (magic methods).\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 5: Environment \u0026amp; Package Management via AI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Master the ecosystem. Use AI to generate 'requirements.txt' and 'pyproject.toml' files. Learn to construct prompts that help you choose between libraries (e.g., Requests vs. HTTPX) and provide terminal commands for managing virtual environments (venv, poetry, or conda) directly through natural language.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eWill AI-generated code make me a \"lazy\" programmer?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            On the contrary, this course treats AI as a mentor, not a replacement. We focus on \"Explanatory Prompting,\" where the AI must justify every line of code it writes. This forces you to engage with the logic and underlying Pythonic principles, actually deepening your understanding faster than manual rote learning.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eWhat if the AI suggests outdated or insecure Python libraries?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            This is a core part of our training. You will learn to use \"Constraint Prompting\" to specify the Python version (e.g., 3.12+) and demand the use of secure, modern libraries. We also teach you how to prompt the AI to perform a security audit on its own suggestions.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eDo I need to be a senior developer for this course?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            This course assumes you have a basic understanding of programming logic (variables, loops, logic). While tailored for experienced devs, it is accessible to anyone who has finished a basic coding bootcamp in another language.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eAre there practical coding labs included?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            Yes. The course features integrated Skillsoft labs where you will be given a \"broken\" or \"non-idiomatic\" Python script and must use a sequence of AI prompts to refactor, debug, and optimize it into a production-ready solution.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757072044357,"sku":null,"price":329.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/prompt_PY_bad2a342-95cd-44d1-9d85-4f67bb39546e.webp?v=1748029033"},{"product_id":"prompt-engineering-for-statistics-and-machine-learning","title":"Prompt Engineering for Statistics and Machine Learning","description":"\u003ch2 class=\"dt-heading-xl\"\u003eMaster the Algorithmic Dialogue: Bridging Statistical Rigor and Generative AI for Data Science\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003e\n    The \"Prompt Engineering for Statistics and Machine Learning\" program is a specialized technical track designed for data scientists and researchers who aim to leverage Large Language Models (LLMs) as high-powered analytical co-pilots. Powered by Skillsoft, this course moves beyond conversational AI to explore how structured prompting can automate the machine learning lifecycle—from exploratory data analysis (EDA) and feature engineering to model selection and hyperparameter tuning. You will master the art of \"grounding\" LLMs in mathematical truth, ensuring that AI-generated statistical interpretations are not only coherent but mathematically sound. By integrating techniques like Program-Aided Language Models (PAL) and advanced Chain-of-Thought reasoning, this training empowers you to build sophisticated, AI-augmented workflows that accelerate discovery while maintaining strict scientific integrity.\n\u003c\/div\u003e\n\n\u003cdiv class=\"dt-grid-v7\"\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eWho is this for?\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003eData Scientists:\u003c\/strong\u003e Professionals looking to automate boilerplate code for model training, evaluation, and visualization.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eMachine Learning Engineers:\u003c\/strong\u003e Specialists aiming to use LLMs for rapid prototyping of neural architectures and loss functions.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eQuantitative Researchers:\u003c\/strong\u003e Individuals needing to translate complex statistical hypotheses into executable Python or R scripts via AI.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eBusiness Intelligence Analysts:\u003c\/strong\u003e Lead analysts who want to use natural language to perform advanced predictive forecasting and anomaly detection.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eAI Researchers:\u003c\/strong\u003e Academics and industry pros exploring the intersection of symbolic logic and probabilistic generative models.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003eAI-Augmented Data Scientist:\u003c\/strong\u003e Leveraging LLMs to accelerate the research-to-production pipeline for predictive models.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eMLOps Engineer (GenAI Focus):\u003c\/strong\u003e Designing automated pipelines that use prompt-driven agents for model monitoring and retraining.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eStatistical Programming Lead:\u003c\/strong\u003e Overseeing the integration of AI-generated code into validated clinical or financial reporting environments.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eData Architect:\u003c\/strong\u003e Blueprinting systems that use RAG to inject proprietary domain knowledge into statistical modeling tasks.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eTechnical AI Consultant:\u003c\/strong\u003e Advising firms on how to safely integrate generative tools into their specialized data science stacks.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n\u003c\/div\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eCourse Curriculum\u003c\/h3\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 1: Prompting for Exploratory Data Analysis (EDA) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Learn to use LLMs to \"interrogate\" your data. Master the art of prompting for automated summary statistics, identifying distribution skews, and generating complex visualization code (Matplotlib, Seaborn, Plotly) from natural language. Focus on using AI to suggest potential correlations and outliers that require further investigation.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 2: Feature Engineering \u0026amp; Data Preprocessing \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Transform raw data into predictive power. Master prompts for automated handling of missing values, encoding categorical variables, and scaling numerical features. Explore advanced prompting techniques for \"feature ideation,\" where the LLM suggests new domain-specific features based on your dataset’s metadata.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 3: Program-Aided Language Models (PAL) for Math \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Overcome the \"math gap\" in LLMs. Learn to implement Program-Aided Language (PAL) prompting, forcing the model to solve statistical problems by generating and executing Python code rather than relying on probabilistic text prediction. This ensures 100% accuracy in complex calculations and statistical tests.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 4: Model Selection \u0026amp; Hyperparameter Optimization \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Let AI assist in the hunt for the optimal model. Learn to write prompts that compare various algorithms (XGBoost vs. LightGBM vs. Random Forest) for specific use cases. Master prompt-driven scripts for GridSearch and RandomSearch, and learn to interpret model evaluation metrics (F1-score, ROC-AUC) using AI-augmented narratives.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 5: Interpretable AI \u0026amp; Statistical Validation \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Focus on the \"Black Box\" problem. Use LLMs to generate SHAP and LIME explanations for your models. Learn to prompt for rigorous statistical validation, including p-value interpretation, confidence interval generation, and identifying potential algorithmic bias through automated auditing prompts.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eCan LLMs actually do math and statistics accurately?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            By default, LLMs are not calculators and can make errors in arithmetic. However, this course teaches you \"Program-Aided\" prompting, where the AI writes and runs code to perform the math. This combines the reasoning of the AI with the absolute precision of a Python interpreter.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eDo I need to be an expert in Python or R for this course?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            An intermediate understanding of Python and basic statistical concepts (mean, variance, regression) is required. The goal of the course is to show you how to use AI to augment these skills, but you must be able to verify and validate the code the AI generates.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eHow does this differ from a general Prompt Engineering course?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            General courses focus on creative writing or basic tasks. This course is strictly technical, focusing on code generation, statistical logic, data structure manipulation, and the integration of AI into the professional Data Science workflow.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eAre there practical ML labs included?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            Yes. This Skillsoft-powered training includes integrated labs where you will use prompts to build a complete end-to-end Machine Learning model—from a raw CSV file to a deployed prediction endpoint—using AI for every major step of the process.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757073879365,"sku":null,"price":329.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/prompt_ML_82c4c647-58ee-464f-b462-f07a6ce52e62.webp?v=1748029039"},{"product_id":"prompt-engineering-with-generative-ai-tools","title":"Prompt Engineering with Generative AI Tools","description":"\u003ch2 class=\"dt-heading-xl\"\u003eUnlock the Full Potential of LLMs: Master the Science and Art of Professional Prompt Engineering\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003e\n    The \"Prompt Engineering with Generative AI Tools\" program is a technical deep-dive into the most critical skill of the 21st century: the ability to communicate precisely with Large Language Models (LLMs). Powered by Skillsoft, this course transitions you from basic chatbot interactions to engineering sophisticated, context-aware prompts that drive enterprise-grade results. You will explore the cognitive architecture of models like GPT-4o, Claude 3.5, and Gemini 2.0, mastering advanced techniques such as Chain-of-Thought (CoT) reasoning, Few-Shot prompting, and the implementation of Retrieval-Augmented Generation (RAG). In an era where AI productivity defines success, this training ensures you can automate complex workflows, generate high-fidelity code, and mitigate risks like hallucination and bias with surgical precision.\n\u003c\/div\u003e\n\n\n\n\u003cdiv class=\"dt-grid-v7\"\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eWho is this for?\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003eSoftware Developers:\u003c\/strong\u003e Looking to 10x their coding efficiency by using AI for boilerplate generation, refactoring, and complex debugging.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eData Analysts:\u003c\/strong\u003e Professionals aiming to use natural language to automate SQL generation, data cleaning, and insight extraction.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eContent Architects:\u003c\/strong\u003e Creative leads who need to build reusable prompt templates for high-scale, brand-consistent content production.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eIT Strategists:\u003c\/strong\u003e Leaders tasked with implementing AI governance and creating internal \"prompt libraries\" for organizational use.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eAI Enthusiasts:\u003c\/strong\u003e Individuals from any background looking to monetize their ability to solve complex problems through AI interaction.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n    \u003cdiv class=\"dt-glass-panel-v7\"\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n            \u003cli\u003e\n\u003cstrong\u003ePrompt Engineer:\u003c\/strong\u003e Designing and optimizing the instructions that power customer-facing AI applications and internal tools.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eAI Implementation Specialist:\u003c\/strong\u003e Bridging the gap between business needs and AI capabilities through expert workflow design.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eGenerative AI Consultant:\u003c\/strong\u003e Advising enterprises on how to reduce operational overhead by integrating LLMs into existing tech stacks.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eConversational Designer:\u003c\/strong\u003e Crafting the persona, logic, and safety guardrails for next-generation AI agents and chatbots.\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eAI Solutions Architect:\u003c\/strong\u003e Blueprinting complex systems that combine RAG, vector databases, and multi-step prompt chains.\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n\u003c\/div\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eCourse Curriculum\u003c\/h3\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 1: Foundations of Generative AI \u0026amp; Tokenization \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Understand what's happening \"under the hood.\" Learn how Transformer models process text, the concept of tokens and context windows, and why the structure of your input changes the probability of the model's output. This module establishes the technical baseline needed for precision engineering.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 2: Advanced Prompting Techniques \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Master the professional toolkit. Dive into Zero-Shot and Few-Shot prompting. Learn \u003cstrong\u003eChain-of-Thought (CoT)\u003c\/strong\u003e to force models to \"think out loud,\" and \u003cstrong\u003eSelf-Consistency\u003c\/strong\u003e to verify outputs. Explore techniques like \"Role-Prompting\" and \"Output Formatting\" to ensure the AI speaks in the exact JSON, SQL, or Markdown you require.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 3: Prompt Engineering for Developers (Code \u0026amp; Data) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Turn your IDE into a powerhouse. Learn to write prompts that generate production-ready code, unit tests, and documentation. Discover how to use AI as a \"Rubber Duck\" for debugging complex logic and how to leverage LLMs for transforming messy data into structured formats.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 4: RAG, Vector Databases \u0026amp; Context Injection \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Break the knowledge barrier. Learn how Retrieval-Augmented Generation (RAG) allows you to feed your own private data into an LLM. This module covers the integration of vector databases (like Pinecone or Weaviate) and how to manage \"Context Stuffing\" while staying within token limits.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eModule 5: Ethics, Security \u0026amp; Prompt Injection \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n        Harden your AI implementations. Learn about the risks of \u003cstrong\u003ePrompt Injection\u003c\/strong\u003e and \"jailbreaking\" attempts. Understand how to identify and mitigate model hallucinations, bias, and privacy leaks. This module focuses on the \"Red Teaming\" mindset required to build safe, enterprise-grade AI applications.\n    \u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eWhat is a \"Prompt Engineer\" and is it a real job?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            Yes. As enterprises integrate AI, they need specialists who can translate business requirements into technical instructions that LLMs can execute reliably. It combines elements of programming, linguistics, and logic, and is currently one of the highest-paying roles in the tech industry.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eDo I need to know how to code to take this course?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            While basic coding knowledge (Python\/JavaScript) helps you get more out of the API and automation modules, the core principles of Prompt Engineering are based on logic and language. This course is designed to be accessible to technical and non-technical professionals alike.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eWhat is \"Hallucination\" and can it be stopped?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            Hallucination occurs when an AI generates confident but false information. While it cannot be 100% eliminated, this course teaches you \"grounding\" techniques, such as RAG and \"Chain-of-Verification,\" that drastically reduce these errors by forcing the model to cite specific data sources.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n    \u003cdetails class=\"dt-faq-item-v7\"\u003e\n        \u003csummary\u003eDoes this course cover specific tools like ChatGPT or Midjourney?\u003c\/summary\u003e\n        \u003cdiv class=\"dt-faq-answer\"\u003e\n            We focus primarily on text-based LLMs (ChatGPT, Claude, Gemini, Llama), as these are the drivers of business automation. However, the principles of structured prompting you learn here are directly applicable to image generation tools like Midjourney and Stable Diffusion.\n        \u003c\/div\u003e\n    \u003c\/details\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757075026245,"sku":null,"price":329.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/prompt_tools_a70cb897-44dd-4371-9a26-d04404a970c7.webp?v=1748029043"},{"product_id":"the-generative-ai-cloud-odyssey-exploring-aws-azure-and-gcp","title":"The Generative AI Cloud Odyssey: Exploring AWS, Azure, and GCP","description":"\u003ch2 class=\"dt-heading-xl\"\u003eNavigate the Future of Intelligence with the Generative AI Cloud Odyssey\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eThe \"Generative AI Cloud Odyssey: Exploring AWS, Azure, and GCP\" is an elite, immersive journey designed for architects and developers who refuse to be locked into a single ecosystem. Powered by Skillsoft, this cross-platform curriculum provides a comprehensive technical deep-dive into how the three cloud giants—Amazon Web Services, Microsoft Azure, and Google Cloud Platform—approach the generative AI revolution. You will move beyond high-level buzzwords to master the implementation of foundational models using Amazon Bedrock, Azure OpenAI Service, and Google Vertex AI. By comparing the architectural nuances, security frameworks, and orchestration tools of each provider, this odyssey ensures you can design resilient, cost-effective, and truly multi-cloud AI solutions that leverage the unique strengths of the entire global cloud landscape.\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-glass-panel-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eWho is this for?\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003e\n\u003cstrong\u003eCloud Architects:\u003c\/strong\u003e Strategic leads designing multi-cloud AI infrastructures that require high availability and vendor neutrality.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAI\/ML Engineers:\u003c\/strong\u003e Practitioners looking to port models across platforms or integrate cross-cloud APIs into a single application.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eDevOps \u0026amp; MLOps Engineers:\u003c\/strong\u003e Professionals automating the deployment, monitoring, and scaling of LLMs across diverse environments.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTechnical Decision Makers:\u003c\/strong\u003e Leaders evaluating the cost-to-performance ratio and security compliance of AWS, Azure, and GCP for GenAI projects.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFull-Stack Developers:\u003c\/strong\u003e Coders building AI-augmented apps who need to understand the nuances of various Cloud AI SDKs.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-glass-panel-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003e\n\u003cstrong\u003eGenerative AI Cloud Architect:\u003c\/strong\u003e Blueprinting cross-platform AI solutions that leverage the best-of-breed services from each provider.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMulti-Cloud AI Developer:\u003c\/strong\u003e Building production-grade applications that seamlessly switch between Bedrock, Azure OpenAI, and Vertex AI.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAI Solutions Consultant:\u003c\/strong\u003e Guiding enterprises through the selection and migration process of cloud-based generative AI workloads.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMLOps Specialist:\u003c\/strong\u003e Standardizing the model lifecycle and observation practices across a fragmented multi-cloud landscape.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eCloud Security Engineer (AI Focus):\u003c\/strong\u003e Implementing unified security baselines and data residency controls for global AI deployments.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eCourse Curriculum\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eModule 1: Foundations of the Cloud GenAI Landscape \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eEstablish a universal baseline. Understand the core principles of Generative AI, foundational models (LLMs, Diffusion, Multimodal), and the shift from discriminative to generative modeling. This module provides a high-level comparison of the AI philosophies and primary service offerings of AWS, Azure, and GCP.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eModule 2: Deep Dive into Amazon Web Services (AWS) GenAI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eMaster the AWS approach to \"democratizing AI.\" Explore Amazon Bedrock and SageMaker JumpStart. Learn to work with models from Anthropic (Claude), Meta (Llama), and Amazon (Titan). Focus on AWS-specific capabilities like Bedrock Knowledge Bases for RAG and security integration via IAM and VPC isolation.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eModule 3: Harnessing Microsoft Azure OpenAI \u0026amp; Cognitive Services \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLeverage the Microsoft-OpenAI partnership. This module covers the Azure OpenAI Service, including access to GPT-4o and DALL-E. Learn to integrate Azure Bot Service and Azure Machine Learning for enterprise chatbots. Explore the tight integration with Microsoft 365 and the specialized security of Azure AI Content Safety.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eModule 4: Innovation with Google Cloud Platform (GCP) Vertex AI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eUnlock Google's deep intelligence legacy. Master Vertex AI and the Generative AI Studio. Learn to use Gemini models for multimodal reasoning and text-to-speech tasks. Explore GCP’s unique advantages in data analytics integration (BigQuery ML) and rapid prototyping tools for language and image generation.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eModule 5: Multi-Cloud Orchestration, Security \u0026amp; Governance \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThe ultimate synthesis. Learn to orchestrate LLM calls across clouds using frameworks like LangChain. Compare the cost governance, monitoring (CloudWatch vs. Azure Monitor vs. Cloud Logging), and ethical AI frameworks of all three providers to build a responsible, enterprise-grade AI strategy.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-faq-item-v7\" open=\"\"\u003e\n\u003csummary\u003eWhat are the prerequisites for the Cloud AI Odyssey?\u003c\/summary\u003e\n\u003cdiv class=\"dt-faq-answer\"\u003eCandidates should have a fundamental understanding of cloud computing concepts and experience with at least one major cloud provider (AWS, Azure, or GCP). A basic grasp of Python and data analysis principles is highly beneficial for the technical labs and API integration modules.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-faq-item-v7\"\u003e\n\u003csummary\u003eDoes this course focus on one specific cloud provider more than others?\u003c\/summary\u003e\n\u003cdiv class=\"dt-faq-answer\"\u003eNo. The core mission of the Odyssey is to provide an objective, balanced exploration of all three major providers. While Google Cloud is used for several deep-dive prototyping modules, the course ensures equal technical weight is given to AWS Bedrock and Azure OpenAI to support multi-cloud proficiency.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-faq-item-v7\"\u003e\n\u003csummary\u003eWhat is \"RAG\" and does this course cover it across all clouds?\u003c\/summary\u003e\n\u003cdiv class=\"dt-faq-answer\"\u003eRetrieval-Augmented Generation (RAG) is a technique used to provide AI models with specific, private data to improve accuracy. Yes, this course covers how to implement native RAG solutions using Bedrock Knowledge Bases (AWS), Cognitive Search (Azure), and Vertex AI Search (GCP).\u003c\/div\u003e\n\u003c\/details\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757088788805,"sku":null,"price":329.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/aicloud_90a4fb81-a75f-46ef-a0ba-855c72df552a.webp?v=1748029102"},{"product_id":"ai-for-data-analytics-bi-learning-kit","title":"AI for Data Analytics and BI Learning Kit","description":"\u003cdiv class=\"dt-product-description-v7\"\u003e\n  \u003ch2 class=\"dt-heading-xl\"\u003eAI for Data Analytics and BI Learning Kit\u003c\/h2\u003e\n\n  \u003cdiv class=\"dt-body-premium\"\u003e\n    The AI for Data Analytics and BI Learning Kit helps learners build practical skills at the intersection of generative AI, analytics and business intelligence. This training focuses on using AI to improve data workflows, accelerate reporting tasks and turn complex datasets into clearer business insights.\n    \u003cbr\u003e\u003cbr\u003e\n    Based on the provided course content, the training supports professionals who want to use prompt engineering, AI-assisted SQL, Power BI capabilities and automated narrative insights to work faster and communicate data more effectively. It is a strong fit for analysts, BI professionals, technical decision-makers and teams exploring AI-driven reporting workflows.\n    \u003cbr\u003e\u003cbr\u003e\n    This product provides training only and does not include a certification exam voucher.\n  \u003c\/div\u003e\n\n  \u003cdiv class=\"dt-container-v7\"\u003e\n    \u003cdiv class=\"dt-grid-v7\"\u003e\n      \u003cdiv\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eWho is this training for\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n          \u003cli\u003eData analysts automating repetitive data and reporting tasks with AI\u003c\/li\u003e\n          \u003cli\u003eBI developers exploring AI-enhanced dashboards and analytics workflows\u003c\/li\u003e\n          \u003cli\u003eData scientists using large language models to speed up SQL and analysis work\u003c\/li\u003e\n          \u003cli\u003eBusiness managers who need to understand AI opportunities and risks in reporting\u003c\/li\u003e\n          \u003cli\u003eIT strategists leading AI-driven analytics adoption across teams\u003c\/li\u003e\n        \u003c\/ul\u003e\n      \u003c\/div\u003e\n\n      \u003cdiv\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n          \u003cli\u003eAI Data Analyst\u003c\/li\u003e\n          \u003cli\u003eBI Architect\u003c\/li\u003e\n          \u003cli\u003eData Operations Lead\u003c\/li\u003e\n          \u003cli\u003eAnalytics Consultant\u003c\/li\u003e\n          \u003cli\u003eInsights Engineer\u003c\/li\u003e\n        \u003c\/ul\u003e\n      \u003c\/div\u003e\n    \u003c\/div\u003e\n  \u003c\/div\u003e\n\n  \u003ch3 class=\"dt-heading-section\"\u003eCourse Modules\u003c\/h3\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003ePrompt Engineering for Data Professionals \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Learn how prompt engineering supports analytics work such as summarization, idea generation, information extraction and better communication in technical and business contexts.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eAI-Powered Code Generation and SQL \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Build practical skills in using generative AI to support SQL writing, code explanation, troubleshooting and faster analytics workflows across technical tasks.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eAdvanced Machine Learning in Power BI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Explore how Power BI can support predictive analysis, advanced visuals and deeper business insight workflows through AI-related features and model-driven reporting.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eText and Vision Analytics for BI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Learn how AI can support analytics beyond structured tables, including sentiment analysis, key phrase extraction, language tasks and image-related classification workflows.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eAutomated Insights and Smart Narratives \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Understand how AI can help generate natural language summaries, support self-service analytics and make business insights easier to understand for wider audiences.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003ch3 class=\"dt-heading-section\"\u003eCareer Opportunities\u003c\/h3\u003e\n\n  \u003cdiv class=\"dt-body-premium\"\u003e\n    This learning kit supports professionals who want to strengthen analytics, reporting and BI skills with generative AI. It is especially useful for teams and individuals who want to reduce manual reporting effort, improve decision support and build faster insight workflows.\n    \u003cbr\u003e\u003cbr\u003e\n    The combination of AI, Power BI and hands-on labs also makes this training relevant for organizations building more advanced analytics capability across business and technical teams.\n    \u003cbr\u003e\u003cbr\u003e\n    For organizations looking to train multiple employees, visit \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eteam training options\u003c\/a\u003e.\n    \u003cbr\u003e\u003cbr\u003e\n    You can also explore more AI-focused options in the \u003ca href=\"https:\/\/www.divitrain.com\/collections\/artificial-intelligence-ai\"\u003eArtificial Intelligence training collection\u003c\/a\u003e.\n  \u003c\/div\u003e\n\n  \u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\n  \u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eDo I need to be a programmer to take this course \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        No. This course is designed to show how AI can also support non-programmers and analysts by helping with code generation, SQL support and structured analytics tasks.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eWhich AI tools are relevant to this learning kit \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        The course focuses on generative AI use cases for analytics and BI workflows. Based on current product naming, Google Bard is now known as Gemini.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eDoes Power BI include AI-driven features \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        Yes. Power BI includes AI-related capabilities such as Q\u0026amp;A, Key Influencers and Smart Narrative style summaries that support faster insight generation.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eHow does this course address AI hallucinations and trust \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        Based on the provided content, the course includes attention to responsible AI use, including verifying outputs, checking AI-generated logic and thinking carefully about accuracy and data sensitivity.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eAre practical labs included \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        Yes. Based on the provided product content, this Learning Kit includes hands-on technical labs for applied analytics scenarios.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n  \u003c\/div\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":57050490732869,"sku":null,"price":349.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/lk_ai_bi.png?v=1770123372"},{"product_id":"prompt-engineering-for-data-science-learning-kit","title":"Prompt Engineering for Data Science - Learning Kit","description":"\u003cdiv class=\"dt-product-description-v7\"\u003e\n  \u003ch2 class=\"dt-heading-xl\"\u003ePrompt Engineering for Data Science Learning Kit\u003c\/h2\u003e\n\n  \u003cdiv class=\"dt-body-premium\"\u003e\n    Prompt Engineering for Data Science is designed to help data professionals use generative AI more effectively across real analytics and machine learning workflows. This training focuses on how structured prompting can support SQL generation, Python tasks, exploratory data analysis, model interpretation and more efficient technical problem-solving.\n    \u003cbr\u003e\u003cbr\u003e\n    Based on the provided course content, the Learning Kit supports professionals who want to integrate LLMs into existing Python, R and SQL workflows in a more practical and controlled way. It is a strong fit for data scientists, data analysts, ML engineers, quantitative researchers and BI professionals working with increasingly complex datasets and reporting demands.\n    \u003cbr\u003e\u003cbr\u003e\n    This product provides training only and does not include a certification exam voucher.\n  \u003c\/div\u003e\n\n  \u003cdiv class=\"dt-container-v7\"\u003e\n    \u003cdiv class=\"dt-grid-v7\"\u003e\n      \u003cdiv\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eWho is this training for\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n          \u003cli\u003eData scientists automating repetitive data wrangling and feature engineering tasks\u003c\/li\u003e\n          \u003cli\u003eData analysts using natural language to generate SQL and Python workflows\u003c\/li\u003e\n          \u003cli\u003eMachine learning engineers integrating LLM output into production and analysis pipelines\u003c\/li\u003e\n          \u003cli\u003eQuantitative researchers exploring synthetic data and AI-assisted reasoning\u003c\/li\u003e\n          \u003cli\u003eBI professionals translating technical findings into clear business summaries\u003c\/li\u003e\n        \u003c\/ul\u003e\n      \u003c\/div\u003e\n\n      \u003cdiv\u003e\n        \u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n        \u003cul class=\"dt-list-premium\"\u003e\n          \u003cli\u003eAI-Augmented Data Scientist\u003c\/li\u003e\n          \u003cli\u003eData Analytics Engineer\u003c\/li\u003e\n          \u003cli\u003eMachine Learning Specialist\u003c\/li\u003e\n          \u003cli\u003ePrompt Engineer\u003c\/li\u003e\n          \u003cli\u003eInsights Automation Lead\u003c\/li\u003e\n        \u003c\/ul\u003e\n      \u003c\/div\u003e\n    \u003c\/div\u003e\n  \u003c\/div\u003e\n\n  \u003ch3 class=\"dt-heading-section\"\u003eCourse Modules\u003c\/h3\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eFoundations of Technical Prompting \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Learn the structure of effective prompts for technical work, including zero-shot and few-shot prompting, persona setting and output constraints that fit data workflows.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eAutomating EDA and Data Cleaning \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Build practical skills in using AI for anomaly detection, missing value handling, feature engineering ideas, exploratory analysis and data explanation for mixed audiences.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003ePrompting for SQL and Code Generation \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Learn how prompt engineering can support text-to-SQL, Python generation, code debugging and more efficient technical problem-solving in analytics environments.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003eAdvanced Reasoning Methods \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Explore advanced prompting methods such as chain-of-thought, least-to-most prompting and code-assisted reasoning for more complex data and statistical tasks.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003cdetails class=\"dt-acc-item-v7\"\u003e\n    \u003csummary\u003ePrompts in the ML Lifecycle \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n    \u003cdiv class=\"dt-acc-content\"\u003e\n      Understand how LLMs can support model documentation, explanation, synthetic data use cases and validation workflows throughout modern machine learning processes.\n    \u003c\/div\u003e\n  \u003c\/details\u003e\n\n  \u003ch3 class=\"dt-heading-section\"\u003eCareer Opportunities\u003c\/h3\u003e\n\n  \u003cdiv class=\"dt-body-premium\"\u003e\n    This Learning Kit supports professionals who want to combine strong data skills with modern AI workflow capabilities. It is especially useful for teams and individuals who want to reduce repetitive work, speed up analysis and improve communication around technical data findings.\n    \u003cbr\u003e\u003cbr\u003e\n    The training is also relevant for organizations that want to build more efficient analytics capability across data science, BI and machine learning teams.\n    \u003cbr\u003e\u003cbr\u003e\n    For organizations looking to train multiple employees, visit \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eteam training options\u003c\/a\u003e.\n    \u003cbr\u003e\u003cbr\u003e\n    You can also explore more AI-focused options in the \u003ca href=\"https:\/\/www.divitrain.com\/collections\/artificial-intelligence-ai\"\u003eArtificial Intelligence training collection\u003c\/a\u003e.\n  \u003c\/div\u003e\n\n  \u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\n  \u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eIs this just a course on how to use ChatGPT \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        No. The course focuses on prompt engineering logic for data science tasks and is relevant to broader LLM-based workflows, not just one tool.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eWill I learn how prompting helps with SQL and Python \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        Yes. Based on the provided content, the training covers text-to-SQL, Python support, debugging and prompt-based technical output generation.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eDo I need to be a senior programmer to take this course \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        No. A basic understanding of Python or SQL is recommended, but the course is designed to help data professionals accelerate their technical workflows with AI.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eDoes this course cover advanced prompting methods \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        Yes. Based on the provided content, the course includes advanced methods such as few-shot prompting, chain-of-thought and least-to-most prompting.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n\n    \u003cdetails class=\"dt-acc-item-v7\"\u003e\n      \u003csummary\u003eHow does this course address privacy and security \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n      \u003cdiv class=\"dt-acc-content\"\u003e\n        The training includes guidance on anonymized prompting and responsible AI use so learners can work more safely with sensitive or proprietary data.\n      \u003c\/div\u003e\n    \u003c\/details\u003e\n  \u003c\/div\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":57051585839429,"sku":null,"price":359.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/prompt-engineering-for-data-science-learning-kit-divitrain.png?v=1771857026"},{"product_id":"microsoft-ai-102-azure-ai-engineer-associate","title":"Microsoft AI-102 Azure AI Engineer Associate Certification Training","description":"\u003cdiv class=\"dt-product-description-v7\"\u003e\n\n\u003ch2 class=\"dt-heading-xl\"\u003eBuild Production-Ready AI Solutions and Pass the AI-102 Exam. Challenge Labs and Practice Exams Included.\u003c\/h2\u003e\n\n\u003cdiv class=\"dt-body-premium\"\u003e\n\u003cp\u003eAs organizations prioritize the integration of Generative AI and intelligent agents, the Microsoft Azure AI Engineer Associate certification has become the industry standard for technical authority. This CertKit delivers the exact skills needed to design and deploy AI models using Azure AI Foundry, Azure OpenAI, and Search services. Prepare to lead enterprise AI initiatives with a structured path that balances deep theory with practical implementation. Access is activated after purchase, allowing you to start your transformation into a specialist role immediately.\u003c\/p\u003e\n\u003c\/div\u003e\n\n\u003cdiv class=\"dt-container-v7\"\u003e\n  \u003ch3 class=\"dt-heading-card\"\u003eWhat is included in this CertKit\u003c\/h3\u003e\n  \u003cul class=\"dt-list-premium\"\u003e\n    \u003cli\u003e\n\u003cstrong\u003e24+ hours of Skillsoft video training\u003c\/strong\u003e covering all 6 exam domains, structured for exam success\u003c\/li\u003e\n    \u003cli\u003e\n\u003cstrong\u003eMeasureUp practice exam with 60 days access\u003c\/strong\u003e, so you know you are ready before exam day\u003c\/li\u003e\n    \u003cli\u003e\n\u003cstrong\u003e7 hours of hands-on Challenge Labs\u003c\/strong\u003e in a virtual environment, so you work through real scenarios before exam day\u003c\/li\u003e\n    \u003cli\u003e\n\u003cstrong\u003eExpert tutor support available 24\/7\u003c\/strong\u003e, so you get answers when you are stuck, not when it is convenient for someone else\u003c\/li\u003e\n    \u003cli\u003e\n\u003cstrong\u003e365-day access\u003c\/strong\u003e with no subscription and no expiry pressure\u003c\/li\u003e\n    \u003cli\u003eOrganizations seeking team-wide certification can explore our \u003ca href=\"https:\/\/www.divitrain.com\/pages\/for-teams\"\u003ecorporate volume solutions\u003c\/a\u003e.\u003c\/li\u003e\n  \u003c\/ul\u003e\n\u003c\/div\u003e\n\n\u003cdiv class=\"dt-container-v7\"\u003e\n  \u003ch3 class=\"dt-heading-card\"\u003eWhy not a cheaper alternative\u003c\/h3\u003e\n  \u003cp\u003eStandard classroom-based AI training typically costs between $1,500 and $2,500 and requires a full week of downtime. This CertKit provides the same high-tier Skillsoft content combined with 7 hours of cloud-hosted labs and industry-standard MeasureUp exams for a fraction of that price. You gain the flexibility to learn while working, backed by 24\/7 support to ensure you never hit a wall. Please note that the exam voucher is purchased separately through Pearson VUE, giving you the freedom to book your test once you have mastered the practice simulations.\u003c\/p\u003e\n\u003c\/div\u003e\n\n\u003cdiv class=\"dt-grid-v7\"\u003e\n  \u003cdiv class=\"dt-container-v7\"\u003e\n    \u003ch3 class=\"dt-heading-card\"\u003eThis CertKit is built for you if\u003c\/h3\u003e\n    \u003cul class=\"dt-list-premium\"\u003e\n      \u003cli\u003eYou are a developer proficient in Python or C# looking to specialize in AI\u003c\/li\u003e\n      \u003cli\u003eYou need to integrate Azure OpenAI and Generative AI into existing enterprise apps\u003c\/li\u003e\n      \u003cli\u003eYou want to master the design of agentic solutions and multi-step intelligent workflows\u003c\/li\u003e\n      \u003cli\u003eYou are an IT professional aiming for a career as an AI or Solutions Engineer\u003c\/li\u003e\n      \u003cli\u003eYou require a realistic lab environment to test AI Search and Vision configurations\u003c\/li\u003e\n    \u003c\/ul\u003e\n  \u003c\/div\u003e\n  \u003cdiv class=\"dt-container-v7\"\u003e\n    \u003ch3 class=\"dt-heading-card\"\u003eRoles you can pursue after AI-102\u003c\/h3\u003e\n    \u003cul class=\"dt-list-premium\"\u003e\n      \u003cli\u003eAzure AI Engineer\u003c\/li\u003e\n      \u003cli\u003eGenerative AI Developer\u003c\/li\u003e\n      \u003cli\u003eIntelligent Applications Engineer\u003c\/li\u003e\n      \u003cli\u003eAI Solutions Architect\u003c\/li\u003e\n      \u003cli\u003eSearch and Relevance Engineer\u003c\/li\u003e\n    \u003c\/ul\u003e\n  \u003c\/div\u003e\n\u003c\/div\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eWhat does the AI-102 exam cover\u003c\/h3\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n  \u003csummary\u003ePlan and manage an Azure AI solution (20–25%) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n  \u003cdiv class=\"dt-acc-content\"\u003eThis domain focuses on designing secure, scalable, and cost-aware AI architectures using Azure AI Foundry and Document Intelligence. You will learn to manage resources, security keys, and billing across the Azure ecosystem.\u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n  \u003csummary\u003eImplement generative AI solutions (15–20%) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n  \u003cdiv class=\"dt-acc-content\"\u003eMaster the deployment of Azure OpenAI models and the application of prompt engineering. This includes grounding models with enterprise data and evaluating model performance using Foundry tools.\u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n  \u003csummary\u003eImplement an agentic solution (5–10%) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n  \u003cdiv class=\"dt-acc-content\"\u003eLearn to design multi-step AI agents that can interact with external APIs and databases. This module covers orchestration using the Foundry Agent Service and advanced reasoning structures.\u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n  \u003csummary\u003eImplement computer vision solutions (10–15%) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n  \u003cdiv class=\"dt-acc-content\"\u003eExplore the implementation of image analysis, facial recognition, and optical character recognition (OCR). You will build pipelines for automated document ingestion and visual data extraction.\u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n  \u003csummary\u003eImplement natural language processing solutions (15–20%) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n  \u003cdiv class=\"dt-acc-content\"\u003eBuild conversational interfaces and text analysis tools. This domain covers sentiment analysis, entity recognition, and the translation of speech and text across global Azure regions.\u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n  \u003csummary\u003eImplement knowledge mining and information extraction (15–20%) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n  \u003cdiv class=\"dt-acc-content\"\u003eMaster Azure AI Search to create hybrid retrieval pipelines that combine keyword and vector search. You will learn to build intelligent indexes that power RAG-based applications.\u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eWhere can AI-102 take your career\u003c\/h3\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n  \u003csummary\u003eCareer paths and next certifications after AI-102 \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n  \u003cdiv class=\"dt-acc-content\"\u003eThe AI-102 is a prerequisite for advanced roles in intelligent automation and enterprise architecture. After AI-102, many professionals move toward \u003ca href=\"https:\/\/www.divitrain.com\/products\/microsoft-dp-100-data-science-solution-on-azure\"\u003eMicrosoft DP-100\u003c\/a\u003e for machine learning model training. For a full structured path, explore our \u003ca href=\"https:\/\/www.divitrain.com\/collections\/microsoft\"\u003eMicrosoft certifications\u003c\/a\u003e.\u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n  \u003csummary\u003eIs the AI-102 exam harder than the AI-900 fundamentals \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n  \u003cdiv class=\"dt-acc-content\"\u003eYes. While the AI-900 focuses on general AI awareness and terminology, the AI-102 is a role-based certification that requires you to demonstrate implementation skills using Python or C#. You must be able to reason about model selection, data governance, and specific API integrations to pass the 100-minute proctored assessment.\u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n  \u003csummary\u003eDo I need to be a data scientist to take the AI-102 exam \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n  \u003cdiv class=\"dt-acc-content\"\u003eNo. This certification is specifically designed for software engineers and developers who want to integrate AI capabilities into their applications. You do not need to train models from scratch. Instead, you use Azure's pre-built APIs and SDKs to deploy intelligent features like vision, search, and generative workflows.\u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n  \u003csummary\u003eWhat programming languages are supported in the labs and exam \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n  \u003cdiv class=\"dt-acc-content\"\u003eMicrosoft recommends proficiency in either Python or C#. The training content and labs provided in this CertKit allow you to work with these languages to interact with Azure AI services via REST APIs and SDKs. Most exam questions will assume you can read and understand one of these two languages in an AI context.\u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n  \u003csummary\u003eIs the exam voucher included and how do I register for the exam \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n  \u003cdiv class=\"dt-acc-content\"\u003eThe exam voucher is not included in this training. The exam is administered globally by Pearson VUE, either at an authorized testing center or via online proctoring. Once your preparation is complete, you register and purchase your exam voucher directly through the official certification or Pearson VUE website.\u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n  \u003csummary\u003eCan my team or organization get certified together \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n  \u003cdiv class=\"dt-acc-content\"\u003eYes. DiviTrain offers volume licensing for teams and organizations looking to upskill at scale. Whether you are certifying a small IT team or rolling out training across departments, our corporate solutions provide flexible access and invoicing options. Visit our \u003ca href=\"https:\/\/www.divitrain.com\/pages\/for-teams\"\u003eFor Teams page\u003c\/a\u003e to learn more.\u003c\/div\u003e\n\u003c\/details\u003e\n\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Microsoft","offers":[{"title":"Default Title","offer_id":57327738749253,"sku":null,"price":399.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/AI102-2.webp?v=1772992288"}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/collections\/Ai_Architect_Career.webp?v=1775221643","url":"https:\/\/www.divitrain.com\/en-eu\/collections\/ai-training-courses.oembed","provider":"DiviTrain.com","version":"1.0","type":"link"}