Course overview
This course webpage will be the main page that will link all the course materials together.
We will employ a flipped classroom approach for this course.
This means that:
- You will study the guided materials on your own (or together with a friend).
- You will then attend the live lecture session for further discussions and clarifications with the instructors.
You will also work on your coursework assignments in your groups, and can drop into the weekly scheduled lab session to seek help from the Tutorial Helpers.
Course structure
| Week | Topic | Lab |
|---|---|---|
| 2 | Machine Learning: The Big Picture | NO LAB |
| 3 | K Nearest Neighbours and Decision Trees | CW1 |
| 4 | Evalation of Machine Learning systems | CW1 |
| 5 | Neural Networks (Part 1) | CW1 |
| 6 | Neural Networks (Part 2) | CW2 |
| 7 | Unsupervised Learning: Clustering & Density Estimation | CW2 |
| 8 | Evolutionary Algorithms | CW2 |
The lab sessions will be held on Wednesdays 9-11am BST/GMT. The live discussion/Q&A sessions will be held on Thursdays 9-10am BST/GMT.
Both sessions will be held on Microsoft Teams. Keep your eyes peeled on Microsoft Teams and Piazza for announcements in case this changes!
Course materials
Guided study materials are available on this webpage in HTML format.
Documents from our modules (e.g. slides) will be posted on Materials. The slides will also act as your lecture notes.
The videos on this webpage are hosted on Panopto, and so are also accessible directly on Panopto.