This repository contains learning materials from a series of Data Science Python study group sessions.
It includes Jupyter notebooks, slide decks (PDF and HTML presentations), and supporting resources (such as code examples, datasets, and images) for each sessiosn.
The content is organized by session number, covering various data science topics and tools in Python, and provides hands-on examples and presentations to help others follow along with the study sessions. Quellenangaben
| Session | Main Materials |
|---|---|
| Session 1 | Slides (PDF) – Introduction slides. (No notebook available) |
| Session 2 | Slides (PDF), Notebook (Jupyter) – Data analysis code and slides. |
| Session 3 | Slides (PDF). (No notebook available) |
| Session 7 | Notebook (Jupyter) – Analysis notebook (e.g. data exploration). (No separate slides found) |
| Session 11: Docker for Data Science | Slides (HTML) – Presentation on setting up Docker for data science. |
| Session 12: Linear Functions from Scratch | Notebook (Jupyter) – Jupyter notebook implementing linear functions for ML. |
| Session 13: NLP Data Scraping (Part 1) | Notebook (Jupyter) – Notebook for NLP data scraping (e.g. Reddit API). |
| Session 14: NLP Data Scraping (Part 2) | Notebook (Jupyter) – Notebook for NLP data scraping (e.g. Twitter API). |