Check out Intro to RL tutorials

Introduction to
Reinforcement Learning

Learn reinforcement learning in 4 weeks. Every week, build an AI which battles to be crowned champion of the cohort in a live competition.

Next cohort starts the week of 2nd January.

A Unique Master's Level Syllabus

Introduction to Reinforcement Learning

Go from 0 to building DQN in a 4-week course taught by experts from DeepMind, Cambridge and Oxford. Implement Reinforcement Learning algorithms in PyTorch in weekly AI-building competitions. Join a cohort of peers to collaborate with and compete against. (exp. time commitment: 7 hrs per week)


  • 12 Handcrafted Tutorials
  • 4 RL Competitions
  • 21 Interactive coding exercises
  • 4 'Office Hours' with Experts
  • Slack Workspace to ask experts any questions
  • Cohort of Peers to Learn and Compete with


  • Basic Python - Loops, Functions & Data Types
  • Basic Probability
Starts 2
Per week for 4 weeks.
Course Organisation

4 Weeks

2nd January to 29th January

Fully remote. Learn from anywhere.
2 live sessions per week:
  • Thurs/Fri: Office Hours (optional, 1 hour)
  • Sunday: Live Competition & Discussion (30 mins)

A new way to learn tech skills

Expert-Crafted Tutorials
Every week starts with 3 tutorials explaining new concepts. Each has Python coding exercises to solve to ensure you can put what you're learning into practice.
Compete Every Week
Apply what you learn each week in the competition. The code is released on Monday, with the submission deadline the following Sunday afternoon.
Live Competition & Discussion
Discuss how each team's solution works and watch the AI's compete! Afterwards, discuss why the winner won & see the code from the experts.

Course Syllabus

Week 1
Reinforcement Learning Fundamentals
What kinds of problems can Reinforcement Learning solve? How does it work? What is the trade-off between exploration and exploitation? The first week answers these questions and more, plus you'll build your first Reinforcement Learning algorithm to play a well-known game and compete amongst the cohort!
Week 2
Learning from Experience
Learn about Monte Carlo and Temporal Difference Learning, two of the key Reinforcement Learning algorithms. You'll code up both of these algorithms and understand how they work, their benefits & drawbacks and how they fit into the overall picture of Reinforcement Learning.
Week 3
Deep Neural Networks with PyTorch
Onto neural networks - from first principles, learn how to design and build Deep Neural Networks with PyTorch. Then apply them using the RL algorithms you've used thus far to build your first Deep Reinforcement Learning agents!
Week 4
Deep Q-Networks
DQN finds approximate solutions to much more complex RL problems than those we've been able to tackle thus far. Plus, it can do so without any prior information about the environment it acts in. We'll learn how to implement DQN and insider information on efficient training.

Learn, Build & Compete
in live AI contests

Online courses are rarely fun. It’s easy to lose motivation and give up.

Delta Academy makes learning RL a blast. In weekly competitions, work as a team to build a game AI and compete against others.
Get up to Speed
Get introduced to new concepts in code through short interactive tutorials that prepare you for the competition at the end of the week.
Team Up
Software is built by teams, not individuals. That's why we encourage collaborating in pairs in competitions. Form your dream-team: bring a friend, or make new ones!
Strive for Victory
Get competitive. Unlike dull online tutorials, where there’s nothing on the line, find yourself ultra-motivated as you strive for victory!

Ready, Set,
in 8 weeks

Go from RL novice to understanding AlphaGo, the system that beat the World Champion in the game of Go, through our two 4-week courses.
Cutting-Edge Code
Learn PyTorch, the machine learning framework used by researchers and practitioners in industry. All exercises and competition code are written in Python 3 with typing hints.
Stuck? Here to help!
Experts are always on hand to immediately answer questions and help you out in the cohort Slack workspace.
Office Hours
Once a week, ask questions in office hours, discuss the content & competition and listen to answers to other cohort members' questions.

What Alumni say

Delta Academy provides a great balance between not being too basic nor too technical for those new to RL, and eases into some sophisticated techniques.

The competition aspect was really unique and provided great motivation to learn the week’s material. I had a lot of fun trying to win and meeting other students. Highly recommend!
Imran Qureshi
Imran Qureshi
AI Product Manager, Google
One of the best classes I've ever taken — it is SO FUN. The competitions are thrilling and hilarious. There is a lot of class camaraderie - people answering questions all the time, and the instructors are truly experts.

This class is one-of-a-kind and I would take any course they create without hesitation.
Siddharth Hiregowdara
Siddharth Hiregowdara
Product Manager,
I really enjoyed Delta Academy.

It has the high quality of top universities, the competitive spirit of Kaggle, and all the conveniences of remote working.
Hristo Buyukliev
Hristo Buyukliev
Senior Data Scientist, TBI Buy
Learning by developing games and joining competitions is probably one of my most fun learning experiences. I was so motivated to keep improving my models and learning from peers.

I can still remember during the four weeks of learning, I was so excited to wake up on Sunday mornings to watch the live competition.
Yiqi Wu
Yiqi Wu
Engineering Manager
Where our Alumni work
Harvard University

Interested in joining the cohort?

Join the 4-Week Intro to Deep Reinforcement Learning cohort starting 2nd January while there are still spaces!
Join Cohort

Frequently asked questions