Resources
Use these to get unstuck fast. If you’re new, start with Colab + GitHub basics first, then move into datasets and templates. Strong projects are usually simple ideas executed clearly.
Learn Colab + GitHub. You need to run code, save work, and submit cleanly.
- Colab intro
- Git/GitHub basics
- Repo structure
Start simple. A clean baseline beats a messy “fancy model.”
- Data loading and cleaning
- Train/val split
- Basic model + metrics
Win on clarity. Show why your approach makes sense and what you learned.
- 1–3 meaningful improvements
- Plots and interpretation
- Clear README + summary
Beginner-friendly intuition for ML, vectors, and learning. Great for your first week.
Official Colab intro. Run notebooks with zero setup.
Intro to how biology + CS combine to answer real questions.
Quick reference for commit, push, branches, and repo structure.
Run Python notebooks in the cloud for ML and analysis.
Version control + collaboration + required submission format.
Dataset hub including biomedical and genomics datasets.
Modern biology notebook + sequences. Useful for bio projects.