Module 10Reinforcement Learning
CartPole Pipeline Project
Build a clean RL project pipeline with configs, logging, and evaluation.
Why this module matters
Project organization is what makes your RL work reproducible and portfolio-ready.
Prerequisites
- ▸ Tianshou basics
Learning objectives
- ▸ Package training and evaluation scripts
- ▸ Log metrics cleanly
- ▸ Compare seeds and checkpoints
Core concepts
Experiment packaging
Evaluation discipline
Checkpoint strategy
Hands-on practice
- ▸ Package a CartPole agent as a reusable project template
Expected output
A reusable RL project skeleton.
Study checklist
- ✅ Package training and evaluation scripts
- ✅ Log metrics cleanly
- ✅ Compare seeds and checkpoints
Common mistakes
- ⚠️ No fixed config snapshots
- ⚠️ No evaluation-only mode
- ⚠️ Mixing environment versions
Module rhythm
- 1. Read the summary and why-it-matters section first.
- 2. Work through concepts before rushing into practice.
- 3. Use the checklist to verify real understanding, not just completion.
How to continue
The final capstone pushes this into a harder continuous-control setting.
Back to course overview →How to use this page well
Treat each module as a compact learning system: understand the intuition, verify the concepts, do one hands-on task, then use the checklist and mistakes section to pressure-test your understanding.