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Lectures and Class Material


  1. Introduction to reproducibility
  2. Terminal and bash
  3. 🌳 Git and GitHub 🌳
  4. 🐍 Introduction to Python 🐍
  5. 🐍 Python toolbox for data analysis 🐍
  6. 🐼 Data wrangling with pandas 🐼
  7. 💥 Classical statistics pitfalls and remedies 💊
  8. 🤖 Machine Learning 1: Supervised Learning 📖
  9. 🤖🤖 Machine Learning 2: Model validation & Unsupervised learning 📖📖
  10. 👀 Introduction to data visualization in Python 🐍
  11. 🐋 Containers 🐋
  12. Large language models
  13. Extras