Course description
Welcome to Demystifying Machine Learning! This is the second edition of this I-Explore STEMM module.
This webpage will be the main portal for the course. Our learning materials can be found here.
Any downloadable materials (e.g. group project specifications) will be made available on Blackboard.
The Ed discussion board is also accessible via Blackboard. We will post all announcements on Ed. We also encourage you to use this forum for any questions or to generate discussions about machine learning among your colleagues.
There are two 'threads' to this course: theory and application.
- The theory bit involves going through some prepared learning materials about the fundamentals of machine learning at your own pace.
- The application aspect is a group project where you identify and solve a real problem (in a field of your choice) with machine learning.
More details about arrangements for the course will be given in the first live session on 18th January 4pm.
Previous editions: [Spring 2022/23]
Course materials
For the 'theory' part of the course, you will go through our self-paced, guided learning materials:
The link can also be accessed via the button on the top right of the webpage.
Schedule
You will consume any of the prepared learning materials in your own time.
Thursdays 4-6pm are reserved for any live activities. These will happen in Huxley (HXLY) Lecture Theatre 340.
These live sessions will vary week by week (or may not even happen) - we may have consultation clinics, discussion sessions, project presentations or guest talks during these sessions. If there are no activities in a specific week, you may use the room for any group project discussions.
The schedule below is provisional and is subject to change.
| Week | Date | Venue | Activity |
|---|---|---|---|
| Week 1 (8/1 - 14/1) |
- | - | - |
| Week 2 (15/1 - 21/1) |
Thu (18/1) 4-6pm | HXLY 340 | Live session: Introduction to module & group project; and Group project initial discussions |
| Week 3 (22/1 - 28/1) |
Thu (25/1) 4-6pm | HXLY 340 | Consultation clinic |
| Week 4 (29/1 - 4/2) |
Thu (1/2) 4-6pm | HXLY 340 | Assessment: Milestone 1 (Project pitch) |
| Fri (2/2) 7pm | - | Assessment: Deadline for peer assessments for project pitch | |
| Week 5 (5/2 - 11/2) |
Early in week | - | Mentors assigned to groups |
| Arranged with mentor | Arranged with mentor | Weekly mentor meeting | |
| Thu (8/2) 4-6pm | HXLY 340 | Guest talk: Norman Di Palo, Imperial College London | |
| Week 6 (12/2 - 18/2) |
Arranged with mentor | Arranged with mentor | Weekly mentor meeting |
| Thu (15/2) 4-6pm | HXLY 340 | Guest talk: Christopher Yim, Machine Learning Engineer at Recycleye | |
| Week 7 (19/2 - 25/2) |
Arranged with mentor | Arranged with mentor | Weekly mentor meeting |
| Thu (22/2) 4-6pm | HXLY 340 | Guest talk: Lee Clewley, Head of Applied AI Group at GlaxoSmithKline | |
| Week 8 (26/2 - 3/3) |
Arranged with mentor | Arranged with mentor | Weekly mentor meeting |
| Thu (29/2) 7pm | - | Assessment: Milestone 2 (Promotional Website) deadline | |
| Thu (29/2) 4-6pm | HXLY 340 | Guest talk: Joe Stacey, Imperial College London | |
| Week 9 (4/3 - 10/3) |
Arranged with mentor | Arranged with mentor | Weekly mentor meeting |
| Thu (7/3) 4pm | - | Assessment: Deadline for peer assessments for promotional website | |
| Thu (7/3) 4-6pm | HXLY 340 | No live session. Venue is free for project meetings. | |
| Week 10 (11/3 - 17/3) |
Arranged with mentor | Arranged with mentor | Weekly mentor meeting |
| Thu (14/3) 4-6pm | HXLY 340 | Assessment: Milestone 3: Technical Presentation | |
| Week 11 (18/3 - 24/3) |
Wed (20/3) 7pm | - | Assessment: Self-reflection Document deadline |
