https://delta-academy.xyz Delta AcademyD cademy Join Cohort Learn AI through games, not lectures 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 13th June. Join Cohort Refer a friend, both get a week free Can't make this cohort?Stay updated via our mailing list Taught by a team from: University of Cambridge Oxford University Google DeepMindDeepMind University College London FiveAI Learn, Build & Compete in live team games Online courses are rarely fun. It's easy to lose motivation and give up. Delta Academy combines live, competitive team coding games with interactive tutorials that teach machine learning to a peer group. Play to win & learn Machine Learning In each Delta Academy competition, 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! [ide_light_2][leaderboard] Reinforcement Learning: Learn from Experience Deep RL is one of the most impactful recent developments in AI. It's responsible for many of the most impressive breakthroughs, including beating the World Champion in Go (AlphaGo). That's why it's the focus of the 4-week Delta Academy course. Cutting-Edge Code Learn PyTorch, the machine learning framework built by Facebook AI Research used by researchers and practitioners in industry. Stuck? Here to help! Experts are always on hand to immediately answer questions and help you out. [alphazero_image] What our users say I get to meet some amazing people and get to see how they would solve a different problem. I love it! The fact that there's a new competition every week compels you to get better fast. I like it very much, since it encourages team work, provides help when needed. It's really focused on teaching as well as solving problems which is unlike Leetcode or something like Codeacademy. On a whole different spectrum Experience. And a shared experience at that. It is not only how I solve a problem, but also how my partner solves it, and how other participants solve it. A Unique Master's Level Course Intro to Deep Reinforcement Learning A unique 4-week course, taught by experts from Oxford, Cambridge and DeepMind. Learn the theory and immediately 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: 10 hrs per week) Includes * 12 Expert-Crafted Interactive Tutorials * 4 RL Competitions to Play * Cohort of Peers to Learn and Compete with * Expert Teaching & Code Review Pre-requisites * Basic Python - Loops, Functions & Data Types * Basic Probability Per week for 4 weeks. $14.99USD Join Cohort Refer a friend, both get a week free Cancel anytime Course Organisation 4 Weeks from June 13th to July 8th Fully remote. Learn from anywhere. [schedule] A new way to learn tech skills Expert-Crafted Tutorials Each week starts with 3 tutorials explaining new concepts, each with problems to solve to ensure you can put what you're learning into practice. Compete Every Week Apply what you've learned each week in the competition. The challenge is released 24 hours before the deadline. We recommend you spend 2 hours on it. Live Discussion & Competition Participate in a live discussion of how each solution works, then watch the AI's compete! Lastly, learn about how to build an optimal solution & see the code from the experts. Meet your Instructors [jimmy] Dr. James Rowland University of Oxford James completed his PhD from the University of Oxford in Neural Computation, studying the paths information takes through the mammalian brain. He's since worked as a Data Scientist at early-stage startups, implementing machine learning models. [MSM_team_p] Henry Pulver Cambridge University, Five AI Henry's Masters' in Machine Learning from Cambridge University was specialised in Reinforcement Learning. He then published papers as a machine learning researcher at the UK's largest autonomous driving startup, Five AI. [MSM_team_p] Dr. Matthew Phillips DeepMind, University College London Matt worked at DeepMind researching Multi-agent Reinforcement Learning and how autonomous agents trade-off collaboration and competition. His PhD from University College London is in the Neuroscience of learning and memory. Course Syllabus Week 1 Reinforcement Learning Fundamentals What kinds of problems can RL solve? How does RL work? What is the tradeoff 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 Monte Carlo, Temporal Difference Learning and TD-Lambda - these approaches are fundamental to RL and you'll write algorithms that use all 3 of these! Week 3 Deep Q-Networks Onto neural networks - DQN allows finding approximate solutions to much more complex problems. We'll learn about how to implement it and insider tips and tricks on training Deep RL. Week 4 Policy Gradient Methods Get acquainted with a 2nd major category of Reinforcement Learning algorithms. Instead of calculating an action-value function and then figuring out which action to take, Policy Gradient Methods directly update the policy to improve. Interested in joining the cohort? Join the 4-Week Intro to Reinforcement Learning cohort starting 13th June while there are still spaces! Join Cohort Refer a friend, both get a week free Any questions? Contact us (c) 2022 Delta Academy, Inc. All rights reserved.