Statistics for Data Science

Course overview

Data science, as well as the related field of machine learning, relies on various abstractions and models that are based on the fundamentals of descriptive and inferential statistics, and utilizes them. Linear regression, for example, is a fundamental tool in data science, and interpreting the results of a regression fit involves analyzing the results of various hypothesis tests. Consequently, an intuitive understanding of basic statistics is very helpful in selecting the right tools from a data scientist's toolbox and also in applying these tools correctly. This learning path aims to equip learners with exactly the necessary level of knowledge and intuition required for such applications. Course content (excerpt): - Data Science Statistics: Simple Descriptive Statistics - Data Science Statistics: Common Approaches to Sampling Data - Data Science Statistics: Inferential Statistics

Upcoming dates

• 2026-08-02T22:00:00.000Z · 2026-08-06T22:00:00.000Z · Dresden · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-08-06T22:00:00.000Z · Rostock · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-08-13T22:00:00.000Z · Bad Nauheim · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-08-13T22:00:00.000Z · Bremerhaven · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-08-06T22:00:00.000Z · Würzburg · Combined Learning