{"product_id":"data-science-python-training-data-analyst-to-data-scientist","title":"Data Science With PYTHON – From Data Analyst To Data Scientist","description":"\u003cp data-mce-fragment=\"1\"\u003eThis journey will first provide a foundation of data architecture, statistics, and data analysis programming skills using Python and R which will be the first step in acquiring the knowledge to transition away from using disparate and legacy data sources. You will then learn to wrangle the data using Python and R and integrate that data with Spark and Hadoop. Next you will learn how to operationalize and scale data while considering compliance and governance. To complete the journey, you will then learn how to take that data and visualize it, to inform smart business decisions.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eThis learning path, with more than 120 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\"\u003eData Science Track 1: Data Analyst\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eData Science Track 2: Data Wrangler\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eData Science Track 3: Data Ops\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eData Science Track 4: Data Scientist\u003c\/strong\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eData Science Track 1: Data Analyst\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eIn this track, the focus is the data analyst role with a focus on: Python, R, architecture, statistics, and Spark.\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\"\u003eData Architecture Primer \u0026amp; Data Engineering Fundamentals\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003ePython for Data Science\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eR for Data Science\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eData Science Statistics\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eAccessing Data with Spark\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eGetting Started with Hadoop\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eHadoop HDFS\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eData Silos, Lakes, \u0026amp; Streams\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: 65 minutes\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003ePractice Labs: Analyzing Data 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\"\u003ePractice performing data analysis tasks using Python by configuring VSCode, loading data from SQLite into Pandas, grouping data and using box plots. Then, test your skills by answering assessment questions after using Python to calculate frequency distribution, measures of center, and coefficient of dispersion. This lab provides access to several tools commonly used in data science, including:\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eVS Code, Anaconda, Jupyter Notebook + Hub, 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\"\u003eData Science Track 2: Data Wrangler\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eIn this track, the focus will be on the data wrangler role. We will explore areas such as: wrangling with Python, Mongo, and Hadoop.\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\"\u003eData Wrangling with Pandas\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eData Wrangler 4\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eData Tools\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMongoDB for Data Wrangling\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eGetting Started with Hive\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eGetting Started with Hadoop\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eAccessing Data with Spark\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eData Lake\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eData Architecture - Deep Dive\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\"\u003e\u003c\/strong\u003e\u003cstrong data-mce-fragment=\"1\"\u003ePractice Labs: Data Wrangling 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 data wrangling tasks including using a Pandas DataFrame to convert multiple Excel sheets to separate JSON documents, extract a table from an HTML file, use mean substitution and convert dates within a DataFrame. Then, test your skills by answering assessment questions after using a Pandas DataFrame to convert a CSV document to a JSON document, replace missing values with a default value, split a column with a delimiter and combine two columns by concatenating text.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e \u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eData Science Track 3: Data Ops\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eThe tracks objective is to help prepare the learner for a Data Ops role with a focus on governance, security, and harnessing volume and velocity.\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\"\u003eDelivering Dashboards\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eCloud Data Architecture\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eCompliance Issues and Strategies \u0026amp; Implementing Governance Strategies\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eData Access \u0026amp; Governance Policies\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eStreaming Data Architectures\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eScalable Data Architectures\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eData Pipeline \u0026amp; Data Sources\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eSecuring Big Data Streams \u0026amp; Harnessing Data Volume \u0026amp; Velocity\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eData Rollbacks\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: Implementing Data Ops 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 data ops tasks with Python including working with row subsets, creating new columns with Regex, performing joins and spreading rows. Then, test your skills by answering assessment questions after working with field subsets and computed columns, and performing set operations and binding rows.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cstrong data-mce-fragment=\"1\"\u003eData Science Track 4: Data Scientist\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eFor this track, the focus will be on the Data Scientist role. Here we will explore areas such as: visualization, APIs, and ML and DL 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\"\u003eData Driven Organizations\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eRaw Data to Insights\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eStorytelling with Data\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003ePython for Data Science\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eR for Data Science\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eAdvanced Visualizations \u0026amp; Dashboards\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eData Insights, Anomalies, \u0026amp; Verification\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eData Research Techniques\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMachine \u0026amp; Deep Learning Algorithms\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eCreating Data APIs Using Node.js\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: Data Visualization 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 data visualization tasks with Python such as creating scatter plots, plotting linear regression, using logistic regression and creating decision tree. Then, test your skills by answering assessment questions after creating time-series graphs, resampling observations, creating histograms and using a grid pair.\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":39259941142614,"sku":"","price":959.2,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/17.png?v=1743543783","url":"https:\/\/www.divitrain.com\/en-eu\/products\/data-science-python-training-data-analyst-to-data-scientist","provider":"DiviTrain.com","version":"1.0","type":"link"}