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Course outline

Download the slides here


Topics

Part 1 - Structure of the brain

Part 1 is about the structure of the brain, how it’s composed of brain cells called neurons, connected via synapses, and divided into different regions. We’ll also talk about how these cells communicate and compute with these signals, and the models we use to try to understand this.

Part 2 - Learning in brain and machine

In part 2, we’ll focus specifically on learning. What we know about how learning happens in the brain, some models of this, and how those models might relate to learning in machines.

Part 3 - Theoretical approaches

Part 3 of the course is about some of the theories that have been proposed about how the brain puts all these mechanisms together. We’ll start from some methodological approaches to how you might go about understanding the brain. These also apply to understanding an artificial neural network. Then we’ll look at some theories of how the brain might be solving some particular sorts of tasks.

Part 4 - Future developments

In the final part, we’ll discuss prospects for the future. We’ll talk about neuromorphic computing, that is, specialised hardware designed to mimic some aspects of how the brain functions. We’ll also talk about some more recent developments in neuroscience that we still don’t quite know what to make of.

Weekly structure

This course uses a flipped classroom approach. That means rather than sitting down and listening to us talk for a couple of hours each week and then go off and try to understand the material on your own, we flip that:

Unfortunately, we won’t be able to do interactive sessions online, but you will have access to all the exercises.

There will also be a discussion group on Teams if you’re at Imperial, or Discord otherwise.

Weekly Structure

Figure 1:N4ML Weekly Structure

Assessment

Finally, for those studying at Imperial this course will be assessed. Details of the assessment is on Canvas.