Robots & AI resources
Incredibly cool, but you have to learn reinforcement learning. These 3 top courses take you from beginner to research. Learn how computers think and robots learn, exploring new environments! π¦Ύ (With a bonus applied course in the making!)
βππ£π©π§π€ π©π€ πππ’π πΌπ ππ£π ππβ by Kaggle
Start with the basics in an applied course in Python.
This course teaches game AI and classic reinforcement learning in an interactive environment.
βππΎπ πΎπ€πͺπ§π¨π π€π£ ππβ by David Silver
The most recommended course on reinforcement learning. Silver is the RL lead in Deepmind and teaches
- π Decision processes
- π Control
- π Policy Gradients
- π Exploration vs Exploitation
and much more.
βπΏπππ₯ ππ π½π€π€π©πππ’π₯β by UC Berkeley
Combining the RL knowledge of the likes of Pieter Abbeel, Karpathy & John Schulman, covering:
- π Deep Q-Learning
- π Pong from Pixels
- π Model-free & -based RL
- π Policy Optimization
& tons more including recent research.
βπΏπππ₯ ππππ£ππ€π§πππ’ππ£π© ππππ§π£ππ£π πΎπ‘ππ¨π¨β by Hugging Face
This is just being released so this is sort of a bonus mention. But I love the depth paired with the applied nature.
- π Deep Q
- π Policy Optimization
- π Decision Transformers
and again so much more!
From intro to recent research, from Deepmind to Openai, these courses cover it all:
- π Intro to Game AI and RL
- π UCL Course on RL
- π Deep RL Bootcamp
- π Huggingface RL Class
Step in where itβs appropriate for you and teach robots by the end of it.
