Machine Learning for Big Data
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Instructor: Dr. Gerit Wagner
Welcome to Machine Learning for Big Data. This course introduces machine learning as a core part of data science for big data contexts, where analysts work with large, high-dimensional, and diverse datasets. Throughout the semester, you will learn how modern machine learning methods complement classical statistics, how to prepare and explore data, and how to build models for classification, prediction, and managerial decision support. The course combines lectures, in-class and home exercises, and practical work with R to help you connect methods and algorithms to real analytical problems.
Sessions
| Status | Title | Date | Time | Location | Materials |
|---|---|---|---|---|---|
| ⚪ Upcoming | Session 1: Big Data Lecture | 2026-09-04 | 10:00–11:30 | S2.11 | Slides |
| ⚪ Upcoming | Session 1: Basics in R Exercise | 2026-09-04 | 11:45–13:15 | S2.11 | Exercise |
| ⚪ Upcoming | Session 2: Analytics Lecture | 2026-09-04 | 14:15–15:45 | S2.11 | Slides |
| ⚪ Upcoming | Session 2: Data Preparation Exercise | 2026-09-04 | 16:00–17:30 | S2.11 | Exercise |
| ⚪ Upcoming | Session 3: EDA Lecture | 2026-09-11 | 10:00–11:30 | S2.11 | Slides |
| ⚪ Upcoming | Session 3: EDA Exercise | 2026-09-11 | 11:45–13:15 | S2.11 | Exercise |
| ⚪ Upcoming | Session 4: ML Baselines (Regression) Lecture | 2026-09-11 | 14:15–15:45 | S2.11 | Slides |
| ⚪ Upcoming | Session 4: ML Baselines (Regression) Exercise | 2026-09-11 | 16:00–17:30 | S2.11 | Exercise |
| ⚪ Upcoming | Session 5: ML Baselines (Classification) Lecture | 2026-09-17 | 10:00–11:30 | S2.07 | Slides |
| ⚪ Upcoming | Session 5: ML Baselines (Classification) Exercise | 2026-09-17 | 11:45–13:15 | S2.07 | Exercise |
| ⚪ Upcoming | Session 6: ML Foundations (Workflow) Lecture | 2026-09-18 | 10:00–11:30 | S2.07 | Slides |
| ⚪ Upcoming | Session 6: ML Foundations (Workflow) Exercise | 2026-09-18 | 11:45–13:15 | S2.07 | Exercise |
| ⚪ Upcoming | Session 7: ML Foundations (Algorithms) Lecture | 2026-09-25 | 10:00–11:30 | S2.07 | Slides |
| ⚪ Upcoming | Session 7: ML Foundations (Algorithms) Exercise | 2026-09-25 | 11:45–13:15 | S2.07 | Exercise |
| ⚪ Upcoming | Session 8: ML for Non-Tabular Data (Text) Lecture | 2026-09-25 | 14:15–15:45 | S2.07 | Slides |
| ⚪ Upcoming | Session 8: ML for Non-Tabular Data (Text) Exercise | 2026-09-25 | 16:00–17:30 | S2.07 | Exercise |
| ⚪ Upcoming | Session 9: ML for Non-Tabular Data (Image, Video, Audio) Lecture | 2026-10-02 | 10:00–11:30 | S2.07 | Slides |
| ⚪ Upcoming | Session 9: Deployment in Organizations Lecture | 2026-10-02 | 11:45–13:15 | S2.07 | Slides |
| ⚪ Upcoming | Session 10: Groupwork Presentation Group presentation | 2026-10-02 | 14:15–15:45 | S2.07 | Slides |
| ⚪ Upcoming | Session 11: Groupwork Presentation Group presentation | 2026-10-02 | 16:00–17:30 | S2.07 | Slides |