Python & data foundations
[Add beginner-friendly Python, NumPy, pandas, statistics, and data-visualization resources.]
Add learning links ↗RESOURCES / YOUR TOOLKIT
Learn something.
Then try it.
A curated library for the curious. Resource cards are placeholders until the club selects its preferred tutorials, datasets, and tools.
Machine learning
[Add materials on model training, feature engineering, evaluation, scikit-learn, and Kaggle.]
Add learning links ↗Generative AI & deep learning
[Add resources on neural networks, LLMs, prompt design, computer vision, and responsible AI.]
Add learning links ↗Dataset of the month
[Dataset name, source, topic, and a small challenge for members to explore.]
Dataset link ↗Tools we use
[Add the club’s recommended stack: notebooks, version control, collaboration, and experiment tracking.]
Explore tools ↗Share a resource
Found something useful? Help the next member learn faster.
Suggest a resource ↗