Machine Learning

Course overview

Structured data processing is the foundation for machine learning projects. The Machine Learning course focuses on automated data pipelines - from harmonization to transformation and targeted provision for model training. Data modeling with SQL A central tool is SQL. The course covers efficient queries, joins, and aggregations to prepare and model large structured datasets effectively for machine learning processes. Data visualization and reporting Power BI is used for the visual presentation of complex analysis results. The course teaches the creation of interactive dashboards and the use of DAX functions to represent data-driven patterns and forecasts in an understandable manner. Exploratory data analysis Another focus is on exploratory data analysis. Statistical methods support the identification of relevant features and the evaluation of variables - a central step for effective feature engineering. Machine learning and modeling The course systematically addresses predictive methods in machine learning. It includes modeling for classification, regression, and clustering, as well as algorithmic optimization and the targeted application of data science insights in concrete application scenarios.

Upcoming dates

• 2026-08-09T22:00:00.000Z · 2027-04-19T22:00:00.000Z · Frankfurt am Main · Hybrid Learning
• 2026-08-09T22:00:00.000Z · 2027-04-19T22:00:00.000Z · Wiesbaden · Hybrid Learning
• 2026-08-09T22:00:00.000Z · 2027-04-19T22:00:00.000Z · Dresden · Hybrid Learning
• 2026-08-09T22:00:00.000Z · 2027-04-19T22:00:00.000Z · Leipzig · Hybrid Learning
• 2026-08-09T22:00:00.000Z · 2027-04-19T22:00:00.000Z · Laatzen bei Hannover · Hybrid Learning