Resources

Supplementary materials for students and instructors.

File / topic	Description
setup-guide.md	Step-by-step environment setup: Python, venv, Jupyter, Git, Ollama, n8n
Readings	See the reading list below (links collected per module)
Cheatsheets	Official docs are the primary reference (links below)

Official documentation

• NumPy: https://numpy.org/doc/stable/
• Pandas: https://pandas.pydata.org/docs/
• Matplotlib: https://matplotlib.org/stable/
• Seaborn: https://seaborn.pydata.org/
• scikit-learn: https://scikit-learn.org/stable/
• PandasAI: https://docs.pandas-ai.com/
• Ollama: https://github.com/ollama/ollama
• n8n: https://docs.n8n.io/

Free books (Module A)

• Python for Data Analysis — W. McKinney: https://wesmckinney.com/book/
• The Art of Data Science — R. Peng & E. Matsui: https://bookdown.org/roback/bookdown-bughunt/

Machine learning (Module B)

• Hands-On Machine Learning (chapters 1–6, 9) — A. Géron
• scikit-learn tutorial: https://scikit-learn.org/stable/tutorial/

AI-assisted workflows (Module C)

• Ollama model library: https://ollama.com/library
• n8n documentation: https://docs.n8n.io/
• PandasAI examples: https://docs.pandas-ai.com/examples
• Responsible AI reading: see the ethics session (W15) and the AI-use policy in ../assessment-plan.md

Work in progress: a per-module annotated reading list (readings.md) will be added as modules begin.