Unit name | Advanced Topics in AI |
---|---|
Unit code | COMSM0028 |
Credit points | 10 |
Level of study | M/7 |
Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
Unit director | Professor. Santos-Rodriguez |
Open unit status | Not open |
Pre-requisites |
None |
Co-requisites |
None |
School/department | School of Computer Science |
Faculty | Faculty of Engineering |
This seminar-style unit introduces advanced and state-of-the-art topics in AI. There will be a mix of presentations by academics and students. The goal of the unit is to both improve the breadth and depth of general AI knowledge and to learn how to process and present scientific material.
The selected topics are chosen to be practically applicable and make students reflect about future research directions. Some topics might not strictly AI but related; they are included to understand the wider context of AI. Examples of topics to be covered in the first year include: Explainable and Interpretable AI; Reinforcement learning; Experimental design; Evaluation and psychometrics.
Upon successful completion of the unit students will be able to:
This unit will be made up of a combination of taught seminars and problem classes.
The unit will be assessed through a presentation (talk) on one or more of the topics covered (30%) and a written report (2,000 words, 70%). Both test all ILOs.
Selected literature, references and online material will be provided at the start of the unit