COMP60012: Introduction to Machine Learning | Department of Computing

Course description

Welcome to Introduction to Machine Learning!

This webpage will be the main portal for the course. Most things you need will be available here. The exceptions are:

PDF of slides and optional tutorial materials: available on Scientia
Announcements and questions/answers/discussions: on EdStem

Classes

At the moment, the plan is to conduct the live classes in hybrid mode. This may change at any point depending on the situation with COVID.

Guided Study Materials

Please go through the study materials before the live interactive session.

Lectures

The live interactive lecture/Q&A session will run on Fridays 16:00-17:00 GMT, from Week 2 onwards. This will be held on site at Huxley 311, with online access (subject to changes).

Lab

The lab sessions will be held on Tuesdays 16:00-18:00 GMT, also from Week 2 onwards. This will be held on site at Huxley 202/206/210, with online support on Microsoft Teams (subject to changes).

The lab sessions are for you to work on your coursework and the optional lab exercises. Tutorial helpers will be available to support you and help you with any queries.

Coursework

There will be two coursework assignments. Please see the schedule below for the deadlines for these.

Weekly Study Page EdStem Scientia CATE Panopto LabTS

Course plan

Week	Date	Lecture	Lab	Coursework
1	10/1/2022	-	-
2	17/1/2022	Machine Learning: The Big Picture	Lab
3	24/1/2022	K Nearest Neighbours and Decision Trees	Lab	Coursework 1 released (Mon 24 Jan)
4	31/1/2022	Evaluation of Machine Learning Systems	Lab
5	7/2/2022	Neural Networks (Part 1)	Lab	Coursework 1 due (Fri 11 Feb 19:00 GMT)
6	14/2/2022	Neural Networks (Part 2)	Lab	Coursework 2 released (Mon 14 Feb)
7	21/2/2022	Unsupervised Learning: Clustering and Density Estimation	Lab
8	28/2/2022	Evolutionary Algorithms	Lab	Coursework 2 due (Fri 4 Mar 19:00 GMT)
9	7/3/2022	Revision	-	-