This week mainly involves learning about foundational concepts in machine learning, for those who are less familiar with them, or want to revise the basics. (For those with little background knowledge, the core readings will take significantly longer than in any other week.) Instead of the group discussions from most weeks, there will be a lecture and group exercises. If you’d like to learn ML in more depth, see the further resources section at the end of this curriculum.

Start with Ngo (2021), which provides a framework for thinking about machine learning, in particular the two key components of deep learning: neural networks and optimisation. For more details and intuitions about neural networks, watch 3Blue1Brown (2017a); for more details and intuitions about optimisation, watch 3Blue1Brown (2017b). OpenAI (2021) showcases one of the most impressive deep learning models so far, using it to write code for a game based on high-level language instructions. Lastly, see von Hasselt (2021) for an introduction to the field of reinforcement learning.