Field Course: Data Science & Machine Learning
This is the schedule and resource page for Field Course (1060): Data Science and Machine Learning, held from October 2026 to January 2027 and taught by Lukas Schmoigl. Everything for the course is collected here: the table below is the schedule for the semester, and each row links to the slides for that lecture along with the other resources that go with it, such as the code files. This page is updated continuously throughout the semester, with further material added whenever it is useful. The Calendar entry in the Directory of Classes also carries the official rooms and times. Registration and deregistration run through LPIS, and grades are entered on Canvas. For more information on the course’s content and grading check out the Lecture Pitch. Questions are welcome by Mail.
| Date | Topic | Content Details | Resources |
|---|---|---|---|
| 2026-10-02 | Coding Setup | VS Code / Git / Quarto | 🖥️ 💾 🔗 |
| 2026-10-09 | Databases and APIs | Parquet / DuckDB / SQL / REST APIs | 🖥️ 💾 💾 |
| 2026-10-16 | Webscraping | HTML / CSS / JavaScript / Rvest / Selenium | 🖥️ 📓 💾 📁 |
| 2026-10-30 | Assignment I / Quiz I | Presentations / Discussions / Quiz | |
| 2026-11-06 | Data Visualization | Tufte’s Principles / Grammar of Graphics / Observable / Vega-Lite | 🖥️ 📓 |
| 2026-11-13 | Decision Tree Learning & Bias-Variance Trade-Off | Decision Tree Learning / Bias-Variance Trade-Off / Coefficient Shrinkage | 🖥️ 📓 |
| 2026-11-20 | Confusion Matrix & Cross Validation | Confusion Matrix / Receiver Operating Characteristic / Cross Validation | 🖥️ 📓 |
| 2026-12-04 | Assignment II / Quiz II | Presentations / Discussions / Quiz | |
| 2026-12-11 | Natural Language Processing | Text Mining / Naive Bayes / Support Vector Machine / Ollama / Hugging Face | 🖥️ 📓 |
| 2026-12-18 | Neural Networks | Image as Data / Activation / Gradient Descent / Backpropagation | 🖥️ 📓 |
| 2027-01-08 | Assignment III / Quiz III | Presentations / Discussions / Quiz | |
| 2027-01-15 | Exam | Pen and Paper | 📄 |