Data Science and Analytics

Course overview

The training program "Data Science and Analytics" combines Data Science, modeling and forecasting, and data analysis. The focus is on data foundation and preparation as well as the practical application of the associated technical terms and work steps. Data Science • Process of a Data Science project from the question to the evaluation using practical examples • Data preparation, modeling, and evaluation of models with accompanying exercises • Use of Python and statistical methods including documentation of results • Presentation of results for departments in sequential work steps Modeling and Forecasting • Overview of statistical models and machine learning methods with reference to typical application cases • Creation of training and test data • Evaluation and comparison of models • Interpretation of forecasts for decision-making Data Analysis • Process of data analysis from the question to the result • Methods of descriptive analysis and calculation of key figures • Evaluation of data with suitable tools • Interpretation and documentation of analysis results Data Foundation and Preparation • Data sources, data formats, and data provision • Cleaning and checking data quality • Structuring and transforming data for evaluation • Documentation of data provenance and work steps The training program combines Data Science and modeling and forecasting and imparts knowledge in data analysis as well as data foundation and preparation. The professional relationships are addressed in the context of Data Science and Analytics.

Upcoming dates

• 2026-11-08T23:00:00.000Z · 2027-03-17T23:00:00.000Z · Aachen · Blended Learning
• 2026-11-08T23:00:00.000Z · 2027-03-17T23:00:00.000Z · Berlin · Blended Learning
• 2026-11-08T23:00:00.000Z · 2027-03-17T23:00:00.000Z · Hannover · Blended Learning
• 2026-11-08T23:00:00.000Z · 2027-03-17T23:00:00.000Z · Duisburg · Blended Learning
• 2026-11-08T23:00:00.000Z · 2027-03-17T23:00:00.000Z · München · Blended Learning

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