Course description
Welcome to Demystifying Machine Learning!
This is the very first edition of this I-Explore STEMM module, so congratulations on being our lab rats 🐀pioneers for the course!
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 19th January 4pm.
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.
- The first session (19th Jan) will be at Skempton Building (SKEM) Room 164.
- Weeks 2-5 will be at City and Guilds Building (CAGB) Room 309.
- [UPDATE!] From 23rd Feb onwards, it will at Huxley (HXLY) Lecture Theatre 308.
The schedule below is provisional and is subject to change.
| Week | Date | Venue | Activity |
|---|---|---|---|
| Week 1 (16/1 - 22/1) |
Thu (19/1) 4-6pm | SKEM 164 | Live session: Introduction to module and group project and Group project discussions |
| Week 2 (23/1 - 29/1) |
Thu (26/1) 4-6pm | CAGB 309 | Consultation clinic |
| Week 3 (30/1 - 5/2) |
Thu (2/2) 4-6pm | CAGB 309 | Assessment: Milestone 1 (Project pitch) |
| Fri (3/2) 7pm | - | Assessment: Deadline for peer assessments for project pitch | |
| Week 4 (6/2 - 12/2) |
Early in week | - | Mentors assigned to groups |
| Arranged with mentor | Arranged with mentor | Weekly mentor meeting | |
| Thu (9/2) 4-6pm | CAGB 309 | No live session - use room for your own discussions if needed | |
| Week 5 (13/2 - 19/2) |
Arranged with mentor | Arranged with mentor | Weekly mentor meeting |
| Thu (16/2) 4-6pm | CAGB 309 | No live session - use room for your own discussions if needed | |
| Week 6 (20/2 - 26/2) |
Arranged with mentor | Arranged with mentor | Weekly mentor meeting |
| Thu (23/2) 4-6pm | HXLY 308 | Guest talk: Benedetta Delfino, Machine Learning Tech Lead at Recycleye | |
| Week 7 (27/2 - 5/3) |
Arranged with mentor | Arranged with mentor | Weekly mentor meeting |
| Thu (2/3) 4pm | - | Assessment: Milestone 2 (Promotional Website) deadline | |
| Thu (2/3) 4-6pm | HXLY 308 | Guest talk: Joe Stacey, Imperial College London | |
| Week 8 (6/3 - 12/3) |
Arranged with mentor | Arranged with mentor | Weekly mentor meeting |
| Thu (9/3) 4pm | - | Assessment: Deadline for peer assessments for promotional website | |
| Thu (9/3) 4-6pm | HXLY 308 | Guest talk: Lee Clewley, Head of Applied AI Group at GlaxoSmithKline | |
| Week 9 (13/3 - 19/3) |
Arranged with mentor | Arranged with mentor | Weekly mentor meeting |
| Thu (16/3) 4-6pm | HXLY 308 | Assessment: Milestone 3: Technical Presentation | |
| Week 10 (20/3 - 26/3) |
Wed (22/3) 7pm | - | Assessment: Self-reflection Document deadline |
Teaching Team
Tom Crossland
Project Mentor
