This is an archived version of the course. Please see the latest version of the course.

Course prerequisites

This is an Introductory Machine Learning course, so we do not require you to have any prior knowledge about Machine Learning.

To get the most out of the course, we recommend that you have some understanding of:

  • Basic algebra
  • Basic calculus (you know what differentiation and integration means)
  • Gaussian (normal) distributions

The course will not require you to derive any mathematical proofs.

For the coursework, you will be expected to program in:

  • Python
  • NumPy
  • PyTorch (optional, for coursework 2)

We provide a Python crash course for either Java or C++ programmers and also a NumPy tutorial, although you will have to allocate extra time to study these. There will also be some optional lab exercises to help guide you in your practical implementations.