Overview
What this challenge is about.
Train a self-play ML agent for a card game, implement CFR, plot exploitability, and play against your agent. Earn a verifiable certificate.
The scenario
The startup (around 12 staff, around 40 university partners worldwide) sells graduate AI workshops; a memorable hands-on demo is its main acquisition lever for new university accounts.
The Brief
What you'll do, and what you'll demonstrate.
Train a self-play CFR agent on a small imperfect-information card game and ship a workshop-ready demo.
Earning criteria — what you'll demonstrate
- Implement CFR or CFR+ for an imperfect-information game
- Measure exploitability as the convergence metric
- Translate self-play training into a visual learning curve students can feel
- Author instructor-grade explanatory material
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Counterfactual Regret Minimization
Apply counterfactual regret minimization to solve real industry problems and demonstrate production-level capability.
- Self Play
Apply self play to solve real industry problems and demonstrate production-level capability.
- Game Theory
Apply game theory to solve real industry problems and demonstrate production-level capability.
- Python
Write clean, efficient Python for data processing, automation, and backend services.
- Reinforcement Learning
Apply reinforcement learning to solve real industry problems and demonstrate production-level capability.
- Educational Content Design
Apply educational content design to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
ML Researcher
Implementing CFR from scratch and reporting honest convergence metrics is the textbook entry-level research project.
This challenge sharpens
- counterfactual-regret-minimization
- self-play
- game-theory
Research Scientist
Reproducing a published algorithm with proper exploitability measurement is the research scientist's first-week deliverable.
This challenge sharpens
- game-theory
- self-play
- counterfactual-regret-minimization
AI Product Designer
Turning a research method into a workshop-ready interactive demo is the AI product designer's bridge from algorithm to learner experience.
This challenge sharpens
- educational-content-design
- python
- reinforcement-learning