{"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\u003cdiv class=\"dt-body-premium\"\u003eDe AWS Certified AI Practitioner AIF-C01 training helpt deelnemers basiskennis op te bouwen van artificial intelligence, machine learning en generative AI binnen het AWS ecosysteem. Deze training is ontwikkeld voor professionals die willen begrijpen hoe AWS AI services zakelijke waarde ondersteunen, praktische AI use cases mogelijk maken en verantwoord kunnen worden ingezet. \u003cbr\u003e\u003cbr\u003eOp basis van de beschikbare cursusinhoud ondersteunt deze training deelnemers die hun inzicht willen versterken in AI en ML concepten, foundation models, responsible AI, AWS governance en het praktische gebruik van AWS services zoals Amazon Bedrock, Amazon SageMaker en Amazon Q. Het is een sterke keuze voor business professionals, projectleiders, analisten en IT-professionals die een gestructureerd startpunt zoeken in AWS AI. \u003cbr\u003e\u003cbr\u003eLet op. De examenvoucher voor de certificering is niet inbegrepen en moet apart worden geboekt via Pearson VUE.\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\"\u003eVoor wie is deze training bedoeld\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eBusiness professionals en beslissers die AI en ML binnen AWS willen verkennen\u003c\/li\u003e\n\u003cli\u003eProjectmanagers en analisten die AI-initiatieven op AWS begeleiden\u003c\/li\u003e\n\u003cli\u003eIT-professionals die een gestructureerd instappunt zoeken in AI op AWS\u003c\/li\u003e\n\u003cli\u003eSales- en marketingspecialisten die AI-productkennis willen verdiepen\u003c\/li\u003e\n\u003cli\u003eTeams die gedeelde AWS AI kennis willen opbouwen over meerdere afdelingen\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eGeschikt voor functies zoals\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\u003ch3 class=\"dt-heading-section\"\u003eAIF-C01 examendomeinen\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eBasisprincipes van AI en ML \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLeer de kernconcepten van artificial intelligence en machine learning, waaronder veelgebruikte leermethoden, de ML lifecycle en de rol van AWS services in praktische AI use cases.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eBasisprincipes van generative AI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eBouw inzicht op in generative AI, large language models, prompt engineering, tokens en de zakelijke waarde van generative AI oplossingen binnen AWS omgevingen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eToepassingen van foundation models \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eVerken hoe foundation models in de praktijk worden toegepast via AWS services zoals Amazon Bedrock en Amazon Q, inclusief evaluatie, aanpassing en geschiktheid voor verschillende use cases.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eRichtlijnen voor responsible AI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eBegrijp de principes van responsible AI, waaronder fairness, uitlegbaarheid, privacy, veiligheid en het belang van het verminderen van bias in AI-systemen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eSecurity, compliance en governance voor AI oplossingen \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLeer hoe dataprivacy, toegangsbeheer, security controls en governance practices worden toegepast op AI en ML workloads die draaien op AWS.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eCarrièremogelijkheden\u003c\/h3\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eDeze training ondersteunt professionals die een sterke basis willen opbouwen in AI en generative AI op AWS zonder dat daar een diepe engineeringachtergrond voor nodig is. De training is vooral waardevol voor teams die een gedeeld begrip nodig hebben van AI terminologie, praktische AWS use cases en verantwoorde AI implementatie. \u003cbr\u003e\u003cbr\u003eDe inbegrepen Practice Labs maken deze training ook relevant voor organisaties die meer praktijkgerichte AWS AI kennis willen opbouwen binnen zowel business als technische functies. \u003cbr\u003e\u003cbr\u003eVoor organisaties die meerdere medewerkers willen trainen, bekijk de \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eteam training opties\u003c\/a\u003e. \u003cbr\u003e\u003cbr\u003eBekijk ook meer AWS trainingen in de \u003ca href=\"https:\/\/www.divitrain.com\/collections\/aws-training-courses\"\u003eAWS training courses collectie\u003c\/a\u003e.\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eVeelgestelde vragen\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIs AIF-C01 bedoeld voor technische of niet-technische professionals \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDeze training is ontwikkeld voor een brede doelgroep en is geschikt voor zowel technische als niet-technische deelnemers die basiskennis van AWS AI willen opbouwen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWat is het verschil tussen deze certificering en AWS Certified Cloud Practitioner \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCloud Practitioner behandelt AWS Cloud in brede zin, terwijl AIF-C01 zich specifiek richt op AI, ML, generative AI en de bijbehorende AWS services.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWelke belangrijke AWS services worden behandeld in deze training \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eBelangrijke services zijn onder andere Amazon Bedrock, Amazon SageMaker en Amazon Q, samen met andere AWS AI mogelijkheden die in de actuele examengids worden genoemd.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eBevat deze training praktijkervaring met AI modellen \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eJa. Op basis van de beschikbare productinformatie bevat deze training Practice Labs voor praktijkgericht leren.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIs het examen inbegrepen bij deze training \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eNee. De examenvoucher voor de certificering is niet inbegrepen. Het examen moet apart worden ingepland via Pearson VUE.\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: AI-Driven Hacking","description":"\u003cdiv class=\"dt-product-description-v7\"\u003e\n\u003ch2 class=\"dt-heading-xl\"\u003eCertified Ethical Hacker CEH v13 Training\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eDe Certified Ethical Hacker CEH v13 training helpt deelnemers praktische offensive security vaardigheden op te bouwen voor ethical hacking, vulnerability assessment en penetration testing. De training richt zich op de belangrijkste fases van ethical hacking, waaronder reconnaissance, scanning, gaining access, maintaining access en rapportage, terwijl deelnemers worden voorbereid op het CEH v13 examen. \u003cbr\u003e\u003cbr\u003eOp basis van de beschikbare cursusinhoud ondersteunt deze training deelnemers die hun kennis willen versterken op het gebied van network scanning, system exploitation, web security, wireless security, cloud security en cryptografie. Het is een sterke keuze voor professionals die willen doorgroeien naar rollen in red teaming, penetration testing en offensive cybersecurity. \u003cbr\u003e\u003cbr\u003eLet op: de examenvoucher voor de certificering is niet inbegrepen en moet apart worden geboekt via Pearson VUE.\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\"\u003eVoor wie is deze training\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eSecurity officers en auditors die hun kennis van ethical hacking willen vergroten\u003c\/li\u003e\n\u003cli\u003eSite administrators die verantwoordelijk zijn voor netwerk- en infrastructuurintegriteit\u003c\/li\u003e\n\u003cli\u003eJunior penetration testers die offensive security vaardigheden ontwikkelen\u003c\/li\u003e\n\u003cli\u003eIT-professionals die willen doorgroeien naar red team of vulnerability assessment rollen\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eVoorbereiding op functies zoals\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eEthical Hacker\u003c\/li\u003e\n\u003cli\u003ePenetration Tester\u003c\/li\u003e\n\u003cli\u003eVulnerability Assessment Analyst\u003c\/li\u003e\n\u003cli\u003eCybersecurity Auditor\u003c\/li\u003e\n\u003cli\u003eSOC Analyst\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\"\u003eCEH v13 Leeronderwerpen\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eReconnaissance and Footprinting \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLeer hoe informatieverzameling ethical hacking trajecten ondersteunt. Dit onderdeel richt zich op het in kaart brengen van digitale footprints, het verzamelen van doelinformatie en het begrijpen van het belang van reconnaissance binnen offensive security processen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eNetwork Scanning and Vulnerability Analysis \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eOntwikkel praktische kennis van scanning en enumeration binnen netwerkomgevingen. Dit onderdeel helpt bij het identificeren van zwakke plekken, het analyseren van scanresultaten en het prioriteren van kwetsbaarheden voor testen en remediation.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eSystem Hacking and Malware Threats \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eBegrijp de offensive security technieken die worden gebruikt om toegang te verkrijgen en te behouden binnen testomgevingen. Dit onderdeel behandelt systeemaanvallen, password attacks, evasion technieken en malware gerelateerde risico’s.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWeb Wireless and IoT Exploitation \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLeer hoe ethical hacking methoden worden toegepast op webapplicaties, draadloze netwerken en verbonden apparaten. Dit onderdeel geeft inzicht in veelvoorkomende attack surfaces en testmethoden.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eCloud Computing and Cryptography \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eVerken beveiligingsconcepten voor cloudomgevingen, encryptie en databescherming. Dit onderdeel helpt deelnemers te begrijpen hoe offensive en defensive security denken wordt toegepast op moderne infrastructuur en gevoelige data.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eCarrièremogelijkheden\u003c\/h3\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eCEH training ondersteunt professionals die een carrière willen opbouwen in ethical hacking, penetration testing, vulnerability assessment en offensive cybersecurity. De training is vooral relevant voor deelnemers die willen doorgroeien van algemene securityrollen naar meer praktische red team of security testing functies. \u003cbr\u003e\u003cbr\u003eDeze training kan organisaties ook helpen interne security testing kennis te versterken en het bewustzijn van offensive security methoden binnen teams te vergroten. \u003cbr\u003e\u003cbr\u003eVoor organisaties die meerdere medewerkers willen trainen, bekijk de \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eteam training opties\u003c\/a\u003e. \u003cbr\u003e\u003cbr\u003eBekijk ook meer cybersecurity trainingen in de \u003ca href=\"https:\/\/www.divitrain.com\/collections\/cyber-security-training\"\u003eCyber Security training collectie\u003c\/a\u003e.\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eVeelgestelde vragen\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWat is Certified Ethical Hacker CEH v13 \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCEH v13 is een ethical hacking training en certificeringstraject dat zich richt op offensive security technieken, praktische labs en gestructureerde ethical hacking workflows.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWat is het verschil tussen CEH en CEH Master \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eCEH Master vereist zowel het CEH theorie-examen als het CEH praktische examen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHeb ik werkervaring nodig voor het CEH examen \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eOfficiële training is een van de manieren om in aanmerking te komen voor het CEH examen. Volgens EC-Council vereist deelname via officiële training geen eerdere cybersecurity werkervaring.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eZijn labs inbegrepen in CEH v13 training \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eJa. De training bevat hands-on labs en CEH v13 wordt door EC-Council gepositioneerd met uitgebreide praktische labomgevingen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIs het CEH examen inbegrepen bij deze training \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eNee. De examenvoucher voor de certificering is niet inbegrepen. Het examen moet apart worden ingepland via Pearson VUE.\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 Training","description":"\u003cdiv class=\"dt-product-description-v7\"\u003e\n\u003ch2 class=\"dt-heading-xl\"\u003eMicrosoft AI-900 Azure AI Fundamentals Certification Training\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eDe Microsoft AI-900 Azure AI Fundamentals training helpt deelnemers basiskennis op te bouwen van artificial intelligence binnen het Microsoft Azure ecosysteem. Deze certificeringstraining introduceert de kernconcepten van AI en de Azure services die worden gebruikt voor machine learning, computer vision, natural language processing, generative AI en responsible AI. \u003cbr\u003e\u003cbr\u003eDe training sluit aan op de Microsoft AI-900 examendoelen en ondersteunt deelnemers die willen begrijpen hoe AI-technologieën kunnen worden toegepast in zakelijke, productgerichte en technische omgevingen. Het is een sterk startpunt voor professionals die Azure AI willen verkennen, beslissers die AI-kansen willen beoordelen en deelnemers die zich willen voorbereiden op meer geavanceerde Microsoft AI-certificeringen. \u003cbr\u003e\u003cbr\u003eLet op: de examenvoucher voor de certificering is niet inbegrepen en moet apart worden geboekt via Pearson VUE.\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\"\u003eVoor wie is deze training\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eIT-beslissers die beter inzicht willen krijgen in de mogelijkheden van AI\u003c\/li\u003e\n\u003cli\u003eDevelopers en data-analisten die starten met Azure AI-concepten\u003c\/li\u003e\n\u003cli\u003eProductmanagers die verantwoordelijk zijn voor AI-functionaliteiten en use cases\u003c\/li\u003e\n\u003cli\u003eStudenten en carrièreswitchers die een sterke basis in AI willen opbouwen\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eVoorbereiding op functies zoals\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eAI Strategy Consultant\u003c\/li\u003e\n\u003cli\u003eJunior Data Scientist\u003c\/li\u003e\n\u003cli\u003eCloud Solution Specialist\u003c\/li\u003e\n\u003cli\u003eAI Product Owner\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\u003ch3 class=\"dt-heading-section\"\u003eAI-900 Exam Domains\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eFundamental AI and Machine Learning Concepts \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLeer wat artificial intelligence is en hoe veelvoorkomende AI-workloads moderne zakelijke en technische omgevingen ondersteunen. Dit onderdeel behandelt kernconcepten van machine learning zoals regressie, classificatie en clustering, samen met de basisfunctionaliteiten van Azure machine learning.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eComputer Vision Workloads in Azure \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eBegrijp hoe Azure AI services visuele data kunnen verwerken en analyseren. Dit onderdeel introduceert image classification, object detection, optical character recognition en veelvoorkomende computer vision use cases.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eNatural Language Processing and Conversational AI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eVerken hoe Azure AI services sentimentanalyse, entiteitsherkenning, vertaling en conversationele ervaringen ondersteunen. Dit onderdeel introduceert de belangrijkste concepten achter taalgedreven AI-oplossingen en chatbots.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eGenerative AI and Azure OpenAI Service \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLeer de basis van generative AI, large language models en promptgestuurde toepassingen binnen Azure. Dit onderdeel helpt deelnemers te begrijpen hoe generative AI kan worden gebruikt voor tekst-, code- en beeldgeneratie.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eResponsible AI and Ethical Governance \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eOntwikkel inzicht in responsible AI-principes zoals fairness, betrouwbaarheid, privacy, transparantie en accountability. Dit onderdeel richt zich op hoe organisaties AI op een meer ethische en gecontroleerde manier kunnen inzetten.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eCarrièremogelijkheden\u003c\/h3\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eMicrosoft AI-900 wordt veel gebruikt als instappunt voor deelnemers die praktische AI-basiskennis willen opbouwen en willen begrijpen hoe Azure AI services echte zakelijke en technische toepassingen ondersteunen. Het is een sterk startpunt voordat je doorgroeit naar meer geavanceerde Azure AI- en machine learning-certificeringen. \u003cbr\u003e\u003cbr\u003eDeze training is ook waardevol voor teams die een gedeeld begrip nodig hebben van AI-concepten, responsible AI en AI-mogelijkheden binnen Azure, zowel in technische als niet-technische rollen. \u003cbr\u003e\u003cbr\u003eVoor organisaties die meerdere medewerkers willen trainen, bekijk de \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eteam training opties\u003c\/a\u003e. \u003cbr\u003e\u003cbr\u003eBekijk ook meer Microsoft certificeringstrainingen in de \u003ca href=\"https:\/\/www.divitrain.com\/collections\/microsoft\"\u003eMicrosoft certificering training collectie\u003c\/a\u003e.\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eVeelgestelde vragen\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWat is de Microsoft AI-900 Azure AI Fundamentals certificering \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eMicrosoft AI-900 is een basiscertificering gericht op artificial intelligence concepten en Azure AI services, waaronder machine learning, computer vision, natural language processing, generative AI en responsible AI.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHeb ik programmeer- of data science ervaring nodig voor AI-900 \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eNee. AI-900 is toegankelijk opgezet voor beginners en vereist geen geavanceerde programmeer- of data science ervaring.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWelke onderwerpen worden behandeld in AI-900 training \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDe training behandelt AI- en machine learning concepten, computer vision, natural language processing, conversational AI, generative AI en responsible AI.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWat is het verschil tussen AI-900 en AI-102 \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eAI-900 richt zich op basiskennis van AI en Azure AI services, terwijl AI-102 bedoeld is voor deelnemers die AI-oplossingen willen bouwen en implementeren.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIs het AI-900 examen inbegrepen bij deze training \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eNee. De examenvoucher voor de certificering is niet inbegrepen. Het examen moet apart worden ingepland via Pearson VUE.\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\"\u003eVersterk Uw Defensieve Houding met Geavanceerde AI en Generatieve Beveiligingsstrategieën\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eIn een landschap waar cyberdreigingen exponentieel toenemen in complexiteit en snelheid, is de integratie van Artificiële Intelligentie binnen enterprise security niet langer optioneel, maar een strategische noodzaak. Deze training biedt een diepgaande verkenning van hoe AI en Generatieve AI de beveiligingsarchitectuur transformeren, van geautomatiseerde threat hunting tot de detectie van AI-gestuurde phishing-aanvallen. U ontwikkelt de expertise om proactieve verdedigingsmechanismen te implementeren die in staat zijn om in real-time te reageren op onbekende zero-day dreigingen, waarbij de balans tussen innovatie en robuuste governance centraal staat. DiviTrain ondersteunt deze kritieke transitie met premium content die de internationale standaarden van cybersecurity volgt, ondersteund door praktische toepasbaarheid binnen complexe zakelijke infrastructuren.\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-grid-column\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eVoor wie is deze training?\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eChief Information Security Officers (CISOs) die een strategische visie op AI-gestuurde beveiliging willen formuleren.\u003c\/li\u003e\n\u003cli\u003eSecurity Engineers en analisten die verantwoordelijk zijn voor de implementatie van geavanceerde detectie- en responstools.\u003c\/li\u003e\n\u003cli\u003eIT-managers die de impact van Generatieve AI op het aanvalsoppervlak van hun organisatie willen mitigeren.\u003c\/li\u003e\n\u003cli\u003eRisk \u0026amp; Compliance Officers die de ethische en juridische kaders van AI-gebruik binnen cybersecurity moeten waarborgen.\u003c\/li\u003e\n\u003cli\u003eOrganisaties die hun teams collectief willen certificeren (bekijk onze \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003evolume-oplossingen\u003c\/a\u003e).\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-column\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eCarrièreperspectieven\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eAI Security Specialist\u003c\/li\u003e\n\u003cli\u003eSenior Threat Intelligence Analyst\u003c\/li\u003e\n\u003cli\u003eCybersecurity Strategist\u003c\/li\u003e\n\u003cli\u003eSecurity Operations Center (SOC) Lead\u003c\/li\u003e\n\u003cli\u003eInformation Security Manager\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eInhoud van de training\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 1: Fundamenten van AI in de Cybersecurity Context \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eIn dit onderdeel leggen we de basis voor het begrijpen van Machine Learning (ML) en Deep Learning (DL) binnen de beveiligingswereld. U leert over gesuperviseerd en ongesuperviseerd leren voor anomaliedetectie en hoe neurale netwerken worden ingezet om patronen in netwerkverkeer te herkennen die voor menselijke analisten onzichtbaar blijven.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 2: Generatieve AI: Nieuwe Dreigingen en Defensieve Kansen \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDit domein analyseert specifiek de rol van Large Language Models (LLMs) in cybersecurity. U leert hoe aanvallers GenAI gebruiken voor 'deepfake' social engineering en geautomatiseerde malware-ontwikkeling. Aan de defensieve kant ontdekt u hoe GenAI kan helpen bij het genereren van beveiligingsscripts, het samenvatten van incidentrapporten en het versterken van 'security awareness' programma's.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 3: AI-Gestuurde Threat Detection en Incident Response \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eU verdiept zich in de integratie van AI binnen SIEM- en SOAR-platformen. Deze module behandelt hoe AI de 'mean time to detect' (MTTD) en 'mean time to respond' (MTTR) drastisch verlaagt door middel van automatische triage van alerts en geautomatiseerde isolatie van gecompromitteerde systemen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 4: Beveiligen van de AI-Infrastructuur (Adversarial AI) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eHet beveiligen van de AI-systemen zelf is cruciaal. U leert over 'adversarial machine learning', waaronder technieken zoals 'data poisoning', 'model evasion' en 'prompt injection'. Dit hoofdstuk biedt praktische kaders om de integriteit en betrouwbaarheid van uw eigen AI-modellen en data-pipelines te waarborgen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 5: Governance, Ethiek en Compliance in een AI-Tijdperk \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eIn de laatste module focussen we op de zakelijke en juridische aspecten. U leert hoe u een AI-security beleid opstelt dat voldoet aan de EU AI Act en GDPR-richtlijnen. We behandelen de ethische overwegingen rondom bias in beveiligingsbeslissingen en hoe u transparantie waarborgt binnen AI-gestuurde beveiligingsprocessen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eVeelgestelde vragen\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe kan Generatieve AI de efficiëntie van mijn security-team verhogen? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eGeneratieve AI kan fungeren als een krachtvermenigvuldiger voor analisten door complexe logbestanden in natuurlijke taal samen te vatten, suggesties te doen voor remediëringstappen en automatisch documentatie te genereren voor incidenten. Hierdoor kunnen senior analisten zich focussen op strategische taken in plaats van repetitief handmatig werk, wat de algehele responstijd van de enterprise aanzienlijk verbetert.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWat zijn de grootste risico's van het implementeren van AI in enterprise security? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDe grootste risico's zijn 'false positives', waarbij legitiem verkeer als dreiging wordt gemarkeerd, en de afhankelijkheid van modellen die vatbaar zijn voor 'adversarial attacks'. Daarnaast is dataprivacy een zorg: het trainen van modellen op gevoelige bedrijfsdata vereist strikte governance om datalekken te voorkomen. Deze training besteedt uitgebreid aandacht aan het mitigeren van deze specifieke risico's.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIs dit examen internationaal erkend en hoe wordt het afgenomen? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDiviTrain volgt de internationale standaarden van Skillsoft en toonaangevende cybersecurity-instituten. Voor formele certificering werken wij samen met partners zoals Pearson VUE. Onze training bereidt u voor op de nieuwste specialistische examens op het gebied van AI-security. Let op: examenvouchers zijn niet inbegrepen en dienen apart te worden aangeschaft via het officiële boekingsplatform.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe ondersteunt DiviTrain zakelijke beslissers bij team-certificering? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eWij begrijpen dat security-transformatie een collectieve inspanning is. Voor organisaties bieden wij volume-voordelen en directe zakelijke facturatie aan. Onze trainingen helpen om een uniforme verdedigingslijn te creëren waarbij elk teamlid de nieuwste AI-concepten begrijpt en toepast. Bezoek onze \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eFor Teams pagina\u003c\/a\u003e voor een voorstel op maat van uw organisatie.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eMoet mijn team al experts zijn in data science om deze training te volgen? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eNee, deze training is specifiek ontworpen voor cybersecurity-professionals. Hoewel we de noodzakelijke wiskundige en technische fundamenten van AI behandelen, ligt de nadruk op de praktische en strategische toepassing binnen security operations. Een basiskennis van netwerken en algemene cybersecurity-concepten is voldoende om de volledige waarde uit dit curriculum te halen.\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":"Generatieve AI Business Transformation Training","description":"\u003ch2 class=\"dt-heading-xl\"\u003eLeid de Fundamentele Bedrijfstransformatie met Generatieve AI\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eDe integratie van Generatieve AI is geen louter technologische upgrade; het is een fundamentele herziening van de manier waarop waarde wordt gecreëerd en geleverd binnen de moderne enterprise. Deze training biedt zakelijke beslissers en strategen de kaders om een holistische AI-transformatie te leiden, variërend van het identificeren van high-impact use cases tot het herinrichten van personeelsstructuren en operationele workflows. U ontwikkelt de expertise om de kloof te dichten tussen technologische potentie en tastbare business-resultaten, waarbij u leert navigeren door complexe vraagstukken rondom ROI, schaalbaarheid en ethische verantwoording. DiviTrain ondersteunt deze strategische transitie met hoogwaardige content die de internationale standaarden van innovatiemanagement volgt, versterkt door diepgaande analyses van succesvolle AI-adoptie in diverse sectoren.\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-grid-column\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eVoor wie is deze training?\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eC-level executives en directeuren die verantwoordelijk zijn voor de strategische koers en innovatie binnen hun organisatie.\u003c\/li\u003e\n\u003cli\u003eBusiness Transformation Managers en Change Leads die de adoptie van AI-gedreven processen moeten begeleiden.\u003c\/li\u003e\n\u003cli\u003eOperations Managers die op zoek zijn naar schaalbare methoden om de productiviteit en efficiëntie te verhogen via AI.\u003c\/li\u003e\n\u003cli\u003eHR-directeuren die de impact van AI op de workforce-planning en talentontwikkeling strategisch willen vormgeven.\u003c\/li\u003e\n\u003cli\u003eOrganisaties die hun managementteams collectief willen certificeren (bekijk onze \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003evolume-oplossingen\u003c\/a\u003e).\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-column\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eCarrièreperspectieven\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eChief AI Officer (CAIO)\u003c\/li\u003e\n\u003cli\u003eDirector of Digital Transformation\u003c\/li\u003e\n\u003cli\u003eStrategic AI Program Manager\u003c\/li\u003e\n\u003cli\u003eOperational Excellence Lead\u003c\/li\u003e\n\u003cli\u003eBusiness Strategy Consultant (AI Focus)\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eInhoud van de training\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 1: De AI-Strategie Formule voor Organisaties \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eIn dit onderdeel leert u hoe u een robuuste AI-strategie formuleert die direct is gekoppeld aan uw kern-bedrijfsdoelstellingen. U krijgt methoden aangereikt om AI-kansen te prioriteren op basis van haalbaarheid en strategische waarde. Tevens behandelen we de verschuiving van experimentele pilot-projecten naar een integrale, schaalbare AI-roadmap die de gehele organisatie beslaat.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 2: Organisatorische Gereedheid \u0026amp; Data-Infrastructuur \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eAI is slechts zo krachtig als de onderliggende data-architectuur. Dit domein behandelt de kritieke vereisten voor data-governance, kwaliteit en toegankelijkheid die nodig zijn voor succesvolle AI-transformatie. U leert hoe u een technologisch ecosysteem bouwt dat gereed is voor grootschalige LLM-integratie, inclusief de overwegingen voor cloud versus on-premise oplossingen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 3: Implementatie van AI-Workflows \u0026amp; Automatisering \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eU verdiept zich in de praktische implementatie van AI binnen diverse business units, van marketing en sales tot supply chain en klantenservice. Deze module verkent de herinrichting van processen waarbij menselijke expertise en machine-intelligentie optimaal samenwerken. De focus ligt op het automatiseren van hoog-volume taken om ruimte te creëren voor strategische creativiteit.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 4: Ethiek, Risicomanagement \u0026amp; Compliance \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eEen cruciaal hoofdstuk over de verantwoorde transformatie. U leert hoe u governance-kaders opstelt om risico's rondom algoritmische bias, privacy en intellectueel eigendom te mitigeren. Tevens wordt er diep ingegaan op de internationale regelgeving, zoals de EU AI Act, en hoe u voldoet aan compliance-eisen zonder de snelheid van innovatie te verliezen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 5: Het Beheren van de Menselijke Factor \u0026amp; Change Management \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDe menselijke factor is de grootste succesfactor van AI-transformatie. U leert hoe u weerstand tegen verandering effectief managet en een cultuur van AI-geletterdheid stimuleert binnen uw teams. We behandelen strategieën voor het upskillen van personeel en het herdefiniëren van rollen, zodat uw organisatie optimaal is toegerust voor de toekomst van werk.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eVeelgestelde vragen\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe verschilt 'AI Business Transformation' van een reguliere AI-cursus? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eWaar een reguliere cursus vaak focust op de technische werking van tools, richt deze training zich op de organisatorische impact. Het gaat niet om het leren gebruiken van een specifieke chatbot, maar om het herontwerpen van uw bedrijfsmodel, uw data-strategie en uw workforce-planning om structureel voordeel te behalen uit Generatieve AI op enterprise-niveau.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWelke concrete resultaten kan ik verwachten na het voltooien van dit traject? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eU beschikt over de tools om een complete AI-roadmap voor uw organisatie op te stellen. Dit omvat een duidelijke analyse van de ROI per use case, een plan voor data-governance en een strategie voor change management. U bent hiermee in staat om de adoptie van AI te versnellen terwijl u de risico's minimaliseert en de operationele efficiëntie meetbaar verhoogt.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIs deze training ook relevant voor kleinere organisaties en MKB? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eAbsoluut. Hoewel de voorbeelden vaak over grotere ecosystemen gaan, zijn de principes van AI-transformatie universeel. Juist voor kleinere organisaties biedt AI de kans om schaalvoordelen te behalen die voorheen onbereikbaar waren. De training helpt u om met beperkte resources de maximale impact te realiseren door de juiste strategische keuzes te maken.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe bereidt DiviTrain mij voor op de officiële certificering en examens? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDiviTrain biedt een premium leerervaring inclusief Live Tutor Support en Practice Labs waar relevant. Wij volgen de internationale standaarden voor IT-leiderschap. Voor formele examens werken wij samen met partners zoals Pearson VUE. Houd er rekening mee dat examenvouchers niet standaard zijn inbegrepen en apart gereserveerd dienen te worden via de officiële kanalen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eBieden jullie ondersteuning bij het trainen van volledige managementteams? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eZeker. Succesvolle transformatie vereist een uniforme visie binnen het gehele leiderschapsteam. Voor zakelijke klanten bieden wij volume-voordelen en de mogelijkheid voor directe zakelijke facturatie. Onze trainingen zijn ontworpen om uw team op één lijn te krijgen wat betreft AI-kansen en risico's. Bezoek onze \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eFor Teams pagina\u003c\/a\u003e voor een voorstel op maat.\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":"\u003ch2 class=\"dt-heading-xl\"\u003eNavigeer door het Transformatieve Landschap van Generatieve AI in 2025\/2026\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eDe introductie van Generatieve AI heeft een nieuwe technologische revolutie ontketend die de manier waarop wij werken, creëren en beslissingen nemen in 2025\/2026 fundamenteel heeft veranderd. Deze training biedt een allesomvattend overzicht van de nieuwste ontwikkelingen binnen Large Language Models (LLMs), beeldgeneratie en multimodale systemen die de huidige markt domineren. U ontwikkelt een diepgaand begrip van de onderliggende architecturen en leert hoe u deze krachtige tools vertaalt naar meetbare efficiëntieverbeteringen binnen uw specifieke zakelijke context. Bij DiviTrain faciliteren we deze kritieke kennisoverdracht met premium content die de internationale standaarden van IT-innovatie volgt, ondersteund door actuele casestudies en expertbegeleiding.\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-grid-column\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eVoor wie is deze training?\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eZakelijke leiders en managers die een strategische visie op de adoptie van AI binnen hun organisatie willen ontwikkelen.\u003c\/li\u003e\n\u003cli\u003eIT-professionals en developers die hun technische horizon willen verbreden met de nieuwste generatieve architecturen.\u003c\/li\u003e\n\u003cli\u003eCreatieve professionals en marketeers die de potentie van AI-gestuurde contentcreatie volledig willen benutten.\u003c\/li\u003e\n\u003cli\u003eProjectmanagers die verantwoordelijk zijn voor het implementeren van innovatieve, AI-gedreven workflows.\u003c\/li\u003e\n\u003cli\u003eOrganisaties die hun teams collectief willen certificeren (bekijk onze \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003evolume-oplossingen\u003c\/a\u003e).\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-column\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eCarrièreperspectieven\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eAI Implementation Specialist\u003c\/li\u003e\n\u003cli\u003eDigital Transformation Manager\u003c\/li\u003e\n\u003cli\u003ePrompt Engineer \u0026amp; Content Strategist\u003c\/li\u003e\n\u003cli\u003eInnovation Lead\u003c\/li\u003e\n\u003cli\u003eAI Strategy Consultant\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eInhoud van de training\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 1: Fundamenten van Generatieve AI (2025 Update) \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eIn dit onderdeel leert u de kernprincipes van Generatieve AI begrijpen en hoe deze verschillen van traditionele machine learning modellen. We behandelen de evolutie van neurale netwerken naar de huidige generatie transformatormodellen. U krijgt inzicht in de terminologie en de technische concepten die noodzakelijk zijn om de mogelijkheden en beperkingen van de huidige technologie te kunnen inschatten.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 2: Large Language Models (LLMs) en Natural Language Processing \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDit domein focust op de werking van toonaangevende taalmodellen zoals de GPT-4 serie, Gemini en Claude. U ontdekt hoe deze modellen getraind worden op enorme datasets en hoe ze mensachtige tekst kunnen genereren, vertalen en samenvatten. Er wordt diep ingegaan op 'zero-shot' en 'few-shot' learning en het belang van contextuele relevantie in zakelijke communicatie.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 3: Multimodale Generatie: Beeld, Video en Audio \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eU maakt kennis met de technologieën achter visuele en auditieve AI-generatie, zoals Diffusion-modellen voor afbeeldingen en de nieuwste video-synthese tools. Deze module verklaart hoe tekstuele prompts worden omgezet in hoogwaardige media. U leert de impact hiervan op industrieën zoals design, media-productie en e-commerce begrijpen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 4: Generatieve AI in de Enterprise en Productiviteit \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDit hoofdstuk vertaalt de technologie naar de praktijk van de moderne werkomgeving. We analyseren use cases zoals AI-gestuurde coding assistants, geautomatiseerde klantenservice en strategische data-analyse. U leert hoe u een AI-roadmap opstelt die gericht is op het verhogen van de operationele snelheid en het verlagen van herhalende werklast binnen teams.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 5: Ethiek, Governance en de Toekomst van AI \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eEen cruciaal onderdeel over de verantwoorde inzet van AI. U leert over bias in algoritmen, intellectueel eigendom en de nieuwste regelgeving zoals de EU AI Act. We bespreken hoe u governance-structuren opzet om veiligheid en privacy te waarborgen, terwijl u anticipeert op de verdere integratie van autonome agenten in het zakelijke ecosysteem.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eVeelgestelde vragen\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWat zijn de belangrijkste updates in de 2025-versie van deze training? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDe 2025-update bevat de nieuwste doorbraken op het gebied van multimodale modellen (die tegelijk tekst, beeld en audio begrijpen) en de opkomst van AI-agenten die zelfstandig taken kunnen uitvoeren. Tevens is de content geactualiseerd met de meest recente juridische kaders en ethische richtlijnen die nu wereldwijd van kracht zijn voor bedrijven.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHeb ik programmeerkennis nodig om deze introductie te volgen? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eNee, deze introductie is specifiek ontworpen om zowel technische als niet-technische professionals een solide fundament te bieden. Hoewel we de onderliggende architectuur bespreken, ligt de focus op het strategisch begrip en de functionele toepassing van Generatieve AI. Voor degenen die dieper willen duiken in de code, bieden wij vervolgtrajecten aan in Python en AI-engineering.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe draagt deze training bij aan mijn professionele certificering? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eHet voltooien van deze training valideert uw kennis van een van de meest gevraagde vaardigheden op de huidige arbeidsmarkt. DiviTrain biedt officieel erkende studiematerialen en ondersteuning via Live Tutor Support. Voor formele examens werken wij samen met internationale partners zoals Pearson VUE, waarbij deze training de ideale basis vormt voor diverse AI-specialisatie-examens.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWorden er praktijkvoorbeelden behandeld die ik direct kan toepassen? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eAbsoluut. De training is doorspekt met real-world casestudies van organisaties die Generatieve AI succesvol hebben geïntegreerd. U krijgt toegang tot Practice Labs waar u kunt experimenteren met prompt engineering en het configureren van AI-workflows, zodat u direct na afloop van de training waarde kunt toevoegen aan uw eigen organisatie of projecten.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eBieden jullie ook volume-licenties aan voor bedrijfsbrede trainingen? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eZeker. DiviTrain is gespecialiseerd in het opschalen van technologische geletterdheid binnen teams. Wij bieden aantrekkelijke volume-voordelen en zakelijke facturatie voor organisaties die hun personeel uniform willen opleiden in de kansen en risico's van AI. Bezoek onze \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eFor Teams pagina\u003c\/a\u003e voor een op maat gemaakt voorstel.\u003c\/div\u003e\n\u003c\/details\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 Training: Integratie \u0026 Architectuur","description":"\u003ch2 class=\"dt-heading-xl\"\u003eSchaal Uw Applicaties met de Architectuur van Morgen: Leveraging Generative AI APIs\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eIn het huidige technologische klimaat is het vermogen om Generatieve AI te ontsluiten via Application Programming Interfaces (APIs) een onderscheidende factor voor innovatieve ondernemingen. Deze training biedt een diepgaande technische verkenning van hoe u toonaangevende modellen zoals ChatGPT, Gemini en Claude naadloos integreert in bestaande software-infrastructuren om intelligente, autonome functionaliteiten te realiseren. U ontwikkelt de expertise om complexe API-architecturen te ontwerpen die niet alleen krachtig en responsief zijn, maar ook voldoen aan de strengste eisen op het gebied van beveiliging, latency en schaalbaarheid. DiviTrain ondersteunt deze technische verdieping met hoogwaardige content, ondersteund door praktische implementatie-scenario's en expertbegeleiding die de internationale standaarden van modern software engineering nauwgezet volgen.\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-grid-column\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eVoor wie is deze training?\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eSoftware Developers en Engineers die hun applicaties willen verrijken met AI-gestuurde functies.\u003c\/li\u003e\n\u003cli\u003eCloud Architecten die verantwoordelijk zijn voor het ontwerpen van schaalbare en veilige AI-integraties.\u003c\/li\u003e\n\u003cli\u003eProduct Owners en technisch leiders die de haalbaarheid van AI-features binnen hun roadmap willen valideren.\u003c\/li\u003e\n\u003cli\u003eDevOps Professionals die de operationele aspecten van AI-API consumptie en monitoring willen beheersen.\u003c\/li\u003e\n\u003cli\u003eOrganisaties die hun teams collectief willen certificeren (bekijk onze \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003evolume-oplossingen\u003c\/a\u003e).\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-column\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eCarrièreperspectieven\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eAI Integrations Engineer\u003c\/li\u003e\n\u003cli\u003eFull-Stack AI Developer\u003c\/li\u003e\n\u003cli\u003eSolutions Architect (AI \u0026amp; Cloud)\u003c\/li\u003e\n\u003cli\u003eMachine Learning Operations (MLOps) Engineer\u003c\/li\u003e\n\u003cli\u003eSenior Software Architect\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eInhoud van de training\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 1: Fundamenten van Generatieve AI API's \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eU leert de basisprincipes van RESTful integraties met LLM-providers. In dit onderdeel behandelen we de anatomie van een API-request, de verschillende model-endpoints en hoe u de juiste parameters selecteert om de balans tussen creativiteit en precisie in de output te waarborgen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 2: Authenticatie, Beveiliging en Key Management \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDit cruciale domein richt zich op het beveiligen van uw API-interacties. U ontwikkelt vaardigheden in het beheren van API-keys via geheimenbeheer (Secrets Management), het implementeren van OAuth-flows waar nodig, en het waarborgen van data-encryptie tijdens transport om enterprise-grade veiligheid te garanderen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 3: Prompt Engineering via Code en Structured Output \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eIn dit onderdeel leert u hoe u prompts programmatisch opbouwt en beheert. De focus ligt op het forceren van gestructureerde data-outputs, zoals JSON of XML, die direct door uw applicatielogica kunnen worden verwerkt. Tevens behandelen we technieken voor context-injectie en 'few-shot' prompting via API-calls.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 4: Multimodale API's en Geavanceerde Integraties \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eU verkent de integratie van multimodale modellen voor beeldgeneratie, audio-analyse en computer vision. U leert hoe u bestanden uploadt naar AI-endpoints, hoe u asynchrone verwerking implementeert voor zware workloads en hoe u verschillende API's combineert in complexe 'agentic' workflows.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 5: Performance Optimalisatie, Rate Limiting en Monitoring \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDit hoofdstuk behandelt de operationele realiteit van AI-API's. U leert strategieën voor caching om kosten te verlagen, het afhandelen van rate limits via exponentiële back-off algoritmen, en het monitoren van tokenverbruik en latency om een consistente gebruikerservaring te bieden.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eVeelgestelde vragen\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWelke programmeertalen worden ondersteund in deze AI API training? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eHoewel de principes van REST-API's universeel zijn, focust deze training zich primair op integraties via Python en JavaScript\/Node.js, aangezien dit de meest gebruikte talen zijn voor AI-implementaties. De concepten rondom JSON-parsing, authenticatie en error-handling zijn echter direct overdraagbaar naar talen zoals C#, Java of Go.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe zit het met de privacy van bedrijfsdata bij het gebruik van publieke AI API's? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDataveiligheid is een kernonderdeel van het curriculum. We behandelen de enterprise-overeenkomsten van providers waarbij data niet wordt gebruikt voor het trainen van publieke modellen. U leert hoe u 'data-at-rest' en 'data-in-transit' beveiliging implementeert en hoe u voldoet aan compliance-standaarden zoals GDPR\/AVG bij het versturen van gebruikersdata naar externe endpoints.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eZijn er extra kosten verbonden aan het gebruik van de API's tijdens de labs? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDiviTrain biedt toegang tot gecontroleerde Practice Labs waar u kunt experimenteren zonder onvoorziene kosten. Voor uw eigen projecten buiten de cursusomgeving bent u zelf verantwoordelijk voor de consumptie-kosten bij providers zoals OpenAI of Microsoft Azure. In de training leert u juist hoe u deze kosten minimaliseert door efficiënte token-management en caching-strategieën.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe bereidt deze training mij voor op internationale certificering? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDe content sluit nauw aan op de eisen voor gespecialiseerde certificeringen van Microsoft (Azure AI Engineer) en Google Cloud (Vertex AI). Onze focus op praktische implementatie via Pearson VUE-standaarden zorgt ervoor dat u niet alleen de theorie kent, maar ook de hands-on vaardigheden bezit die tijdens deze examens en in professionele assessments worden getoetst.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eBiedt DiviTrain zakelijke facturatie voor development teams? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eZeker. Wij ondersteunen IT-organisaties bij het opschalen van hun AI-capaciteiten door middel van volume-voordelen en directe zakelijke facturatie. Onze trainingen zijn ontworpen om uw gehele development team op een uniforme standaard te krijgen wat betreft AI-architectuur en veiligheid. Bezoek onze \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eFor Teams pagina\u003c\/a\u003e voor een voorstel op maat.\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 met Generatieve AI Tools","description":"\u003ch2 class=\"dt-heading-xl\"\u003eBeheers de Taal van AI: Strategische Waardecreatie met Prompt Engineering\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eIn het huidige technologische tijdperk is de kwaliteit van de output van Generatieve AI direct evenredig aan de kwaliteit van de input. Deze training in Prompt Engineering biedt een diepgaande verkenning van de methodieken die nodig zijn om complexe Large Language Models (LLMs) met uiterste precisie aan te sturen voor zakelijke toepassingen. U ontwikkelt de expertise om intenties te vertalen naar gestructureerde prompts die consistentie, veiligheid en relevantie garanderen in elke interactie met AI-systemen. DiviTrain ondersteunt deze kritieke vaardigheidsontwikkeling met hoogwaardige content die de internationale standaarden van AI-interactie volgt, ondersteund door praktische labs en expertbegeleiding die direct toepasbaar zijn in een enterprise-omgeving.\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-grid-column\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eVoor wie is deze training?\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eContent strategen en marketeers die de efficiëntie van hun creatieve processen willen maximaliseren via AI.\u003c\/li\u003e\n\u003cli\u003eSoftware developers en data-analisten die LLMs willen integreren in hun technische workflows en applicatielogica.\u003c\/li\u003e\n\u003cli\u003eBusiness analisten en projectmanagers die complexe data-samenvattingen en rapportages willen automatiseren.\u003c\/li\u003e\n\u003cli\u003eInnovatieleads en strategen die verantwoordelijk zijn voor de adoptie van AI-tools binnen hun organisatie.\u003c\/li\u003e\n\u003cli\u003eOrganisaties die hun teams collectief willen certificeren (bekijk onze \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003evolume-oplossingen\u003c\/a\u003e).\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-column\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eCarrièreperspectieven\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eAI Prompt Engineer\u003c\/li\u003e\n\u003cli\u003eContent Automation Architect\u003c\/li\u003e\n\u003cli\u003eDigital Transformation Specialist\u003c\/li\u003e\n\u003cli\u003eAI Implementation Consultant\u003c\/li\u003e\n\u003cli\u003eBusiness Process Automation Lead\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eInhoud van de training\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 1: Fundamenten van LLM-interactie en Tokenisatie \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eIn dit onderdeel leert u hoe Large Language Models informatie verwerken en hoe tokenisatie de structuur van uw prompts beïnvloedt. U krijgt inzicht in de architectuur van transformatormodellen en de rol van context-windows. Deze module legt de theoretische basis die noodzakelijk is om te begrijpen waarom bepaalde instructies leiden tot specifieke outputs en hoe u hallucinaties van het model kunt minimaliseren.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 2: Geavanceerde Prompting Technieken \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eU verdiept zich in de kernmethodieken van professionele prompting, waaronder Zero-shot, Few-shot en Chain-of-Thought (CoT) prompting. Deze module leert u hoe u stapsgewijze redenering bij het model afdwingt om complexe problemen op te lossen. Tevens behandelen we 'Persona Prompting' en hoe u de toon en expertise van de AI nauwgezet kunt kalibreren voor specifieke zakelijke doelgroepen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 3: Iteratieve Ontwikkeling en Troubleshooting \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003ePrompting is een iteratief proces. In dit domein leert u hoe u de kwaliteit van AI-output systematisch evalueert en verfijnt. We behandelen technieken voor het debuggen van ongewenste resultaten en het implementeren van 'Negative Prompts' om specifieke elementen uit te sluiten. U ontwikkelt een gestructureerde aanpak om prompts te testen op robuustheid en variabiliteit over verschillende modellen heen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 4: Integratie van AI in Enterprise Workflows \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDit hoofdstuk vertaalt prompt engineering naar de operationele praktijk. U leert hoe u prompts bouwt die gestructureerde data (zoals JSON of XML) genereren voor integratie met andere systemen. We verkennen hoe prompt-bibliotheken kunnen worden opgezet binnen teams om herbruikbaarheid en standaardisatie te bevorderen, wat essentieel is voor het schalen van AI-toepassingen binnen een grotere organisatie.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 5: Beveiliging, Ethiek en Prompt Injection \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eEen cruciaal onderdeel over de risico's van AI-interactie. U leert over 'prompt injection' aanvallen en hoe u verdedigingsmechanismen inbouwt om te voorkomen dat modellen gevoelige informatie prijsgeven of hun instructies negeren. We behandelen tevens de ethische kaders rondom bias en intellectueel eigendom, zodat uw AI-strategie voldoet aan de nieuwste compliance-richtlijnen en maatschappelijke normen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eVeelgestelde vragen\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIs Prompt Engineering een tijdelijke trend of een duurzame vaardigheid? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eHoewel AI-modellen steeds intuïtiever worden, blijft de behoefte aan precisie en controle binnen een zakelijke context groeien. Prompt engineering gaat niet alleen over het schrijven van tekst, maar over het begrijpen van de logica achter AI-architecturen. Deze vaardigheid stelt u in staat om complexe automatiseringen te bouwen die verder gaan dan eenvoudige interacties, wat een blijvend concurrentievoordeel oplevert voor zowel individuen als organisaties.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eMoet ik kunnen programmeren om een expert te worden in Prompt Engineering? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eNee, programmeerkennis is geen strikte vereiste voor deze training. De nadruk ligt op linguïstische precisie, logisch redeneren en het begrijpen van model-architecturen. Voor professionals die echter AI via API's willen ontsluiten, biedt de training wel de noodzakelijke kaders voor het genereren van gestructureerde outputs die door code verwerkt kunnen worden. Hierdoor is de training waardevol voor zowel marketeers als engineers.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe bereidt DiviTrain mij voor op de praktische toepassing van deze technieken? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDiviTrain biedt een premium leeromgeving met toegang tot gespecialiseerde Practice Labs. In deze labs experimenteert u direct met verschillende toonaangevende modellen om de effecten van uw prompts in real-time te observeren. Onze Live Tutor Support staat klaar om u te begeleiden bij complexe scenario's, zodat u niet alleen de theorie beheerst, maar ook de praktische finesse ontwikkelt die nodig is op de internationale arbeidsmarkt.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe verloopt het examenproces en ontvang ik een officieel certificaat? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eNa het voltooien van de training kunt u deelnemen aan het assessment om uw vaardigheden te valideren. Voor formele examens werken wij samen met internationale partners via het Pearson VUE netwerk. Houd er rekening mee dat examenvouchers niet standaard zijn inbegrepen bij de cursusprijs en apart gereserveerd dienen te worden. Het succesvol afronden van dit traject levert u een certificering op die uw technische autoriteit in AI-interactie internationaal bevestigt.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWelke zakelijke oplossingen biedt DiviTrain voor het trainen van volledige afdelingen? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eWij ondersteunen organisaties bij het verhogen van de AI-geletterdheid binnen hun gehele personeelsbestand. Voor zakelijke klanten bieden wij aantrekkelijke volume-voordelen en de mogelijkheid voor directe zakelijke facturatie. Dit stelt u in staat om uw team op een uniforme en efficiënte wijze op te leiden in de nieuwste AI-technieken. Voor een voorstel op maat kunt u terecht op onze \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eFor Teams pagina\u003c\/a\u003e.\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":"Generatieve AI Cloud Odyssey: AWS, Azure \u0026 GCP Training","description":"\u003ch2 class=\"dt-heading-xl\"\u003eBeheers de Multicloud AI-Revolutie: Een Strategische Verkenning van AWS, Azure en GCP\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eIn het huidige technologische landschap is de keuze voor een cloud-provider bepalend voor de snelheid en schaalbaarheid van uw AI-innovaties. Deze 'Cloud Odyssey' biedt een diepgaande vergelijking tussen Amazon Web Services (AWS), Microsoft Azure en Google Cloud Platform (GCP), specifiek gericht op hun Generatieve AI-portfolio's. U ontwikkelt de expertise om de architecturale verschillen tussen AWS Bedrock, Azure OpenAI Service en Google Vertex AI te doorgronden, waardoor u gefundeerde beslissingen kunt nemen die de operationele efficiëntie en het competitief voordeel van uw organisatie maximaliseren. DiviTrain ondersteunt deze specialistische groei met hoogwaardige content die de internationale standaarden van cloud-architectuur volgt, versterkt door real-world scenario's en expertbegeleiding op topniveau.\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-grid-column\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eVoor wie is deze training?\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eCloud Architecten en Solution Designers die een multicloud-strategie voor AI-implementaties willen ontwikkelen.\u003c\/li\u003e\n\u003cli\u003eTechnical Leads en CTO's die de sterke en zwakke punten van de 'Big Three' providers willen evalueren voor enterprise-gebruik.\u003c\/li\u003e\n\u003cli\u003eDevOps en MLOps Engineers die verantwoordelijk zijn voor het uitrollen en monitoren van Large Language Models in diverse cloud-omgevingen.\u003c\/li\u003e\n\u003cli\u003eStrategisch adviseurs die organisaties begeleiden bij complexe cloud-migraties en AI-gebaseerde digitale transformaties.\u003c\/li\u003e\n\u003cli\u003eOrganisaties die hun teams collectief willen certificeren (bekijk onze \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003evolume-oplossingen\u003c\/a\u003e).\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-column\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eCarrièreperspectieven\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eMulticloud AI Architect\u003c\/li\u003e\n\u003cli\u003ePrincipal Cloud Engineer\u003c\/li\u003e\n\u003cli\u003eDirector of AI Infrastructure\u003c\/li\u003e\n\u003cli\u003eCloud Strategy Consultant\u003c\/li\u003e\n\u003cli\u003eSenior MLOps Architect\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eInhoud van de training\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 1: AWS Bedrock en het Amazon AI-Ecosysteem \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eIn dit onderdeel verkennen we de unieke 'serverless' benadering van AWS Bedrock. U leert hoe u toegang krijgt tot een breed scala aan Foundation Models van toonaangevende aanbieders zoals Anthropic, AI21 Labs en Amazon zelf. We behandelen de integratie met AWS SageMaker, de beveiligingsprotocollen van AWS KMS en hoe u schaalbare AI-applicaties bouwt binnen de vertrouwde AWS-infrastructuur.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 2: Azure OpenAI Service en de Microsoft Cloud \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eU verdiept zich in de nauwe samenwerking tussen Microsoft en OpenAI. Deze module behandelt de enterprise-functies van de Azure OpenAI Service, inclusief data-isolatie, regionale beschikbaarheid en de integratie met het bredere Azure-ecosysteem zoals Azure AI Search en Semantic Kernel. U leert hoe u de kracht van GPT-modellen ontsluit met de veiligheidsgaranties die zakelijke klanten van Microsoft verwachten.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 3: Google Cloud Vertex AI en de Model Garden \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDit domein focust op de innovatiekracht van Google Cloud. U ontdekt de mogelijkheden van Vertex AI en de 'Model Garden', waar u toegang krijgt tot Gemini en diverse open-source modellen. We behandelen de geavanceerde tuning-opties, de integratie met BigQuery voor data-driven AI en de specifieke voordelen van Google's TPU-infrastructuur voor grootschalige model-training en inferentie.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDomein 4: Multicloud Governance en Model Selectie Strategieën \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eIn de laatste module leert u hoe u een vendor-onafhankelijke strategie opstelt. We analyseren kostenstructuren, latency-overwegingen en compliance-eisen over de verschillende platformen heen. U ontwikkelt een raamwerk voor 'Model Selection' waarbij u leert welk platform het meest geschikt is voor specifieke zakelijke behoeften, van cost-efficiency tot maximale creatieve output.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eVeelgestelde vragen\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWelke cloud-provider is momenteel het meest geavanceerd voor Generatieve AI? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eEr is geen eenduidig antwoord, aangezien elk platform unieke sterktes heeft. Azure blinkt uit in de integratie met OpenAI-modellen en zakelijke software. AWS biedt de meest flexibele 'model-as-a-service' benadering met Bedrock, terwijl Google Cloud (GCP) superieur is in multimodale mogelijkheden en data-integratie met Gemini. Deze training helpt u de juiste keuze te maken op basis van uw specifieke architecturale eisen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe vergelijken de kosten zich tussen AWS Bedrock, Azure OpenAI en Vertex AI? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDe prijsmodellen variëren aanzienlijk: waar sommigen rekenen per token (input\/output), gebruiken anderen een combinatie van resource-provisioning en verbruik. In de training behandelen we uitgebreide kostenanalyses en 'FinOps' strategieën voor AI, zodat u onvoorziene uitgaven kunt voorkomen en de ROI van uw cloud-investeringen kunt optimaliseren ongeacht de gekozen provider.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eZijn er praktijkgerichte labs beschikbaar voor alle drie de cloud-platformen? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eJa, DiviTrain biedt toegang tot gespecialiseerde Practice Labs waar u hands-on ervaring opdoet met AWS, Azure en GCP. U leert modellen configureren, API's ontsluiten en beveiligingsinstellingen beheren in realistische omgevingen. Onze Live Tutor Support staat klaar om u te begeleiden bij de specifieke technische uitdagingen die elk ecosysteem met zich meebrengt.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe bereidt deze training mij voor op officiële vendor-certificeringen? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eHoewel deze training een multicloud-focus heeft, dekken de domeinen een groot deel van de stof voor certificeringen zoals de AWS Certified AI Practitioner, Azure AI Engineer Associate en Google Professional Machine Learning Engineer. De examens worden afgenomen via Pearson VUE. Houd er rekening mee dat examenvouchers apart gereserveerd dienen te worden via de officiële kanalen van de betreffende providers.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eBiedt DiviTrain zakelijke oplossingen voor het opleiden van cloud-teams? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eAbsoluut. Wij ondersteunen organisaties bij het transformeren van hun IT-personeel naar multicloud AI-experts. Voor zakelijke klanten bieden wij aantrekkelijke volume-voordelen en de mogelijkheid voor directe zakelijke facturatie. Dit stelt u in staat om uw gehele team op een uniforme standaard te krijgen wat betreft AI-strategie en implementatie. Bezoek onze \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eFor Teams pagina\u003c\/a\u003e voor een voorstel op maat.\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 voor Data Science Training","description":"\u003ch2 class=\"dt-heading-xl\"\u003eMaximaliseer de Slagkracht van AI met Prompt Engineering voor Data Science\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003ePrompt Engineering is uitgegroeid van een handige vaardigheid tot een cruciaal paradigma binnen de data science workflow. Deze specialistische training leert u hoe u Large Language Models (LLM's) zoals GPT-4 en Claude strategisch inzet om complexe data-analyses te versnellen, code-generatie te optimaliseren en geavanceerde machine learning-modellen te verfijnen. Door het combineren van taalkundige precisie met technische data-expertise, transformeert u AI van een eenvoudige assistent naar een krachtige motor voor innovatie en operationele efficiëntie.\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-grid-item\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eVoor wie is deze training?\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003e\u003cstrong\u003eData Scientists:\u003c\/strong\u003e Professionals die hun workflow willen automatiseren en diepere inzichten uit ongestructureerde data willen halen.\u003c\/li\u003e\n\u003cli\u003e\u003cstrong\u003eMachine Learning Engineers:\u003c\/strong\u003e Specialisten die LLM's willen integreren in hun applicaties en de output-kwaliteit willen verhogen.\u003c\/li\u003e\n\u003cli\u003e\u003cstrong\u003eData Analisten:\u003c\/strong\u003e Analisten die complexe SQL-queries en Python-scripts sneller en foutloos willen genereren.\u003c\/li\u003e\n\u003cli\u003e\u003cstrong\u003eAI-Strategen:\u003c\/strong\u003e Managers die de grenzen van generatieve AI binnen hun organisatie willen verkennen en implementeren.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-item\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eCarrièreperspectieven\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eLead Data Scientist (AI-Focused)\u003c\/li\u003e\n\u003cli\u003ePrompt Engineer \/ AI Architect\u003c\/li\u003e\n\u003cli\u003eGenerative AI Specialist\u003c\/li\u003e\n\u003cli\u003eBusiness Intelligence Developer\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\"\u003eInhoud van de training\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eLLM Fundamenten voor Data Science \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eBegrijp de onderliggende architectuur van Transformers en hoe LLM's data interpreteren. Deze module behandelt de beperkingen en mogelijkheden van modellen bij het verwerken van gestructureerde en ongestructureerde datasets.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eAdvanced Prompting Patterns \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eBeheers technieken zoals Chain-of-Thought (CoT), Few-Shot prompting en ReAct-patterns. Leer hoe u de logica van AI-modellen kunt sturen om complexe wiskundige en analytische problemen stap-voor-stap op te lossen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eData Cleaning \u0026amp; Synthetic Data Generation \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eOntdek hoe u prompts gebruikt voor data-imputatie, het opschonen van corrupte datasets en het genereren van hoogwaardige synthetische data voor het trainen van robuuste machine learning-modellen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eCode-optimalisatie en Debugging \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eGebruik LLM's voor het genereren en refactoren van Python, R en SQL-code. Deze module focust op het schrijven van prompts die veilige, efficiënte en gedocumenteerde code opleveren die direct inzetbaar is in productie-omgevingen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eEthiek en AI Governance \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eNavigeer door de ethische uitdagingen van generatieve AI, waaronder bias-detectie, hallucinaties en data-privacy. Leer hoe u verantwoorde prompts ontwerpt die voldoen aan enterprise-compliance standaarden.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eVeelgestelde vragen\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe onderscheidt deze training zich van algemene AI-cursussen? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eIn tegenstelling tot algemene cursussen is dit curriculum specifiek ontworpen voor de technische data-professional. We focussen niet op eenvoudige tekstgeneratie, maar op de integratie van LLM's in de data-pipeline, van exploratieve data-analyse (EDA) tot de implementatie van voorspellende modellen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eZijn er praktijkopdrachten inbegrepen? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eJa, u krijgt toegang tot gespecialiseerde \u003cstrong\u003ePractice Labs\u003c\/strong\u003e van Skillsoft. Hierin past u prompt-technieken direct toe op real-world datasets in een veilige omgeving. Bovendien staat onze \u003cstrong\u003eLive Tutor Support\u003c\/strong\u003e klaar voor hulp bij complexe analytische vraagstukken.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\" open=\"\"\u003e\n\u003csummary\u003eWordt deze vaardigheid getoetst via een officieel examen? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eHoewel Prompt Engineering een relatief nieuw veld is, bereidt deze training u voor op de groeiende reeks AI-certificeringen van vendoren zoals Microsoft en Google. Officiële examinering vindt plaats via de professionele standaard van \u003cstrong\u003ePearson VUE\u003c\/strong\u003e. Let op: specifieke examenvouchers zijn \u003cstrong\u003eniet\u003c\/strong\u003e bij de cursusprijs inbegrepen.\u003c\/div\u003e\n\u003c\/details\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":"\u003ch2 class=\"dt-heading-xl\"\u003eBeheers de Kracht van Azure AI en Transformeer Bedrijfsprocessen met Intelligente Oplossingen\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003eDe AI-102 certificering is de internationale standaard voor IT-professionals die gespecialiseerde AI-oplossingen willen bouwen op het Microsoft Azure-platform. In een wereld waar generatieve AI en automatisering de boventoon voeren, biedt deze training de diepgaande technische expertise die nodig is om cognitieve diensten, bot-frameworks en machine learning-modellen naadloos te integreren. U leert niet alleen hoe u complexe algoritmen implementeert, maar ook hoe u schaalbare en veilige AI-architecturen ontwerpt die directe waarde toevoegen aan moderne enterprise-omgevingen. Door het behalen van dit certificaat positioneert u zichzelf in de voorhoede van de technologische revolutie en bewijst u uw waarde voor organisaties die streven naar digitale innovatie.\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-container-card\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eVoor wie is deze training?\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eSoftwareontwikkelaars die AI-functionaliteit willen integreren in hun applicatiestack.\u003c\/li\u003e\n\u003cli\u003eCloud Solutions Architects die verantwoordelijk zijn voor het ontwerp van intelligente infrastructuren.\u003c\/li\u003e\n\u003cli\u003eData Engineers die de overstap willen maken naar toegepaste kunstmatige intelligentie en Cognitive Services.\u003c\/li\u003e\n\u003cli\u003eIT-professionals die hun expertise in Azure willen verzilveren met een wereldwijd erkend certificaat.\u003c\/li\u003e\n\u003cli\u003eOrganisaties die hun teams collectief willen certificeren (bekijk onze \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003evolume-oplossingen\u003c\/a\u003e).\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-container-card\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eCarrièreperspectieven\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eGecertificeerd Azure AI Engineer Associate\u003c\/li\u003e\n\u003cli\u003eSenior Cloud Developer (AI-Specialisatie)\u003c\/li\u003e\n\u003cli\u003eCognitive Solutions Consultant\u003c\/li\u003e\n\u003cli\u003eAI Infrastructure Architect\u003c\/li\u003e\n\u003cli\u003eLead Developer Generative AI\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eInhoud van de training\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003ePrepare for and Configure an Azure AI Solution \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eIn dit domein leert u de fundamenten van het inrichten van AI-resources binnen de Azure-omgeving. Dit omvat het configureren van beveiliging via Azure Key Vault, het beheren van API-sleutels en het implementeren van Role-Based Access Control (RBAC) om te voldoen aan enterprise compliance-eisen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDeploy and Manage Azure AI Services \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eU verdiept zich in de levenscyclus van AI-diensten, van initiële implementatie tot continue monitoring. Hierbij ligt de focus op kostenbeheer, het gebruik van Azure Monitor voor diagnostiek en het optimaliseren van de prestaties van diverse Cognitive Services onder variërende workloads.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eImplement Content Moderation Solutions \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDeze module behandelt het automatiseren van toezicht op tekstuele en visuele content. U leert hoe u de Azure Content Moderator configureert om ongepaste of gevoelige informatie te detecteren en te filteren, wat essentieel is voor het waarborgen van veilige gebruikersomgevingen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eImplement Computer Vision Solutions \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eHier ontwikkelt u de vaardigheid om visuele data te analyseren en te interpreteren. Onderwerpen zijn onder andere beeldclassificatie, objectdetectie en gezichtsherkenning, waarbij u gebruikmaakt van de Computer Vision API en Custom Vision voor sectorspecifieke toepassingen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eImplement Natural Language Processing Solutions \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDit kritieke onderdeel focust op de interactie tussen mens en machine. U leert hoe u Azure Cognitive Service for Language implementeert voor taken zoals sentimentanalyse, entiteitsherkenning en het bouwen van intelligente vertaaloplossingen voor wereldwijde markten.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eImplement Knowledge Mining Solutions \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eU leert hoe u ongestructureerde data omzet in doorzoekbare kennisbronnen met Azure Cognitive Search. Dit omvat het configureren van indexen, het verrijken van data via AI-vaardigheden en het ontsluiten van diepe inzichten uit complexe documenten en databases.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eImplement Generative AI Solutions \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eIn dit moderne domein staat de implementatie van Large Language Models (LLM's) centraal. U leert hoe u Azure OpenAI Services configureert, prompt engineering toepast en generatieve modellen veilig integreert in bedrijfsapplicaties voor geavanceerde tekst- en codecreatie.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eVeelgestelde vragen\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWat is het verschil tussen AI-102 en de AI-900 training? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eDe AI-900 is een fundamentele training gericht op algemene concepten, terwijl de AI-102 een diepgaand technisch examen is voor professionals. De AI-102 vereist programmeervaardigheden in C# of Python en richt zich op de daadwerkelijke implementatie van AI-architecturen in een productieomgeving.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eBiedt DiviTrain ondersteuning bij de praktijkgerichte opdrachten? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eJa, deze training is inclusief toegang tot Practice Labs en Live Tutor Support. Hiermee kunt u in een beveiligde sandbox-omgeving oefenen met echte Azure-resources, waardoor u de nodige ervaring opdoet voor zowel de praktijk als het officiële examen.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe werkt het examenproces via Pearson VUE? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eNa afronding van de training kunt u zich inschrijven voor het officiële examen bij Pearson VUE. DiviTrain biedt de volledige voorbereiding, maar de examenvoucher is niet standaard inbegrepen. Het examen kan zowel op locatie als online onder toezicht (proctoring) worden afgelegd.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eZijn er extra kosten verbonden aan de Azure-omgeving tijdens de cursus? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eOnze Practice Labs zijn volledig inbegrepen in de cursuskosten, wat betekent dat u geen eigen Azure-abonnement of verbruikskosten hoeft te betalen om de oefeningen te voltooien. Dit biedt een risicovrije omgeving om met complexe AI-services te experimenteren.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHoe kan ik mijn team aanmelden voor deze AI-102 training? \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eVoor organisaties bieden wij gestroomlijnde trajecten met volume-voordeel en zakelijke facturatie. U kunt hiervoor direct contact opnemen met onze consultants via de \u003ca href=\"https:\/\/www.divitrain.com\/nl-nl\/pages\/for-teams\"\u003eFor Teams pagina\u003c\/a\u003e, waar we specifiek ingaan op collectieve opleidingsbehoeften.\u003c\/div\u003e\n\u003c\/details\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\/nl-nl\/collections\/ai-training-courses.oembed","provider":"DiviTrain.com","version":"1.0","type":"link"}