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Unit information: Advanced Topics in AI in 2021/22

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 Dr. Santos-Rodriguez
Open unit status Not open




School/department Department of Computer Science
Faculty Faculty of Engineering

Description including Unit Aims

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.

Intended Learning Outcomes

Upon successful completion of the unit students will be able to:

  1. identify and describe the wider context in which AI systems operate;
  2. demonstrate an understanding of selected topics in advanced AI, such as reinforcement learning and explainable AI;
  3. demonstrate an understanding of selected topics in relevant scientific methodology, such as experimental design and psychometrics;
  4. process and present scientific material to a peer audience.

Teaching Information

Teaching will be delivered through a series of mostly synchronous sessions, including lectures, seminars, practical activities, discussion groups and self-directed exercises.

Assessment Information

1 Summative Assessment, 100% - Coursework. This will assess all ILOs.


If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. COMSM0028).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the Faculty workload statement relating to this unit for more information.

The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.