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Unit information: Research Methods in Interactive Artificial Intelligence in 2022/23

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Research Methods in Interactive Artificial Intelligence
Unit code COMSM0133
Credit points 20
Level of study M/7
Teaching block(s) Teaching Block 4 (weeks 1-24)
Unit director Professor. Peter Flach
Open unit status Not open
Units you must take before you take this one (pre-requisite units)

None

Units you must take alongside this one (co-requisite units)

None

Units you may not take alongside this one

None

School/department School of Computer Science
Faculty Faculty of Engineering

Unit Information

This unit introduces CDT students to a range of research methods in interactive AI, and prepares them to carry out their own research in the Summer Project and subsequent PhD research. Through the unit students will improve the breadth and depth of their general AI knowledge, learn how to process and present scientific material, and how to plan for a larger research project.

Research seminars given by external and internal speakers will serve as exemplars of state-of-the-art AI research. Students will also research selected topics from the literature and present their findings in oral and written form (first deliverable). The topics will be chosen to be practically applicable and make students reflect about future research directions and about their own research. The second deliverable of the unit will be a Project Synopsis that prepares the ground for the Summer Project.

Your learning on this unit

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. process and present scientific material to a peer audience;
  4. demonstrate a technical and methodological understanding of the chosen research topic sufficient to start the Summer Project;
  5. produce a viable plan for successful completion of the Summer Project.

How you will learn

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

How you will be assessed

The unit is assessed through two pieces of coursework:

1. A report of about 10 pages describing background research in a selected topic in Interactive AI (50%, assessing ILOs 1-3).

2. Synopsis of proposed Summer Research Project in the form of a written report of about 5 pages (50%, assessing ILOs 4-5) that includes the following elements:

  • aims and objectives of the project;
  • background and state of the art;
  • deliverables;
  • workplan and timeline

Resources

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. COMSM0133).

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.

Assessment
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.

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