October 28th, 2019: In-term Examination

The in-term examination for this module will take place during the Friday November 15th.

October 21st, 2019: Web-site is fully up-to-date

All teaching materials and code are available on this web-site and it will be updated weekly.

About this Module

Credit Weighting: 5

Pre-requisite(s): None

Co-requisite(s): None

Teaching Method(s): 24 x 1hr(s) Lectures; 9 x 1hr(s) Practicals.

Module Objective: Review and critically analyse the motivating factors, challenges and technical concepts behind artificial intelligence.

Module Content: Topics that may be covered in this module include: the principles, technologies and applications of model-driven versus data-driven AI; the ethics of AI; fair, accountable and transparent AI.

Learning Outcomes: On successful completion of this module, students should be able to:

  • Critically discuss the challenges and opportunities in realising the future of AI.
  • Describe in detail the main principles, technologies and applications of AI.
  • Evaluate AI technologies from a performance but also an ethical viewpoint.

Assessment: Total Marks 100: Continuous Assessment 100 marks (1x Mid-Semester Examination 40 marks, 1 x End of Semester Examination 40 marks, 2 x Laboratory Reports, 10 marks each).

Compulsory Elements: Continuous Assessment.

Penalties (for late submission of Course/Project Work etc.): Work which is submitted late shall be assigned a mark of zero (or a Fail Judgement in the case of Pass/Fail modules).

Pass Standard and any Special Requirements for Passing Module: 40\%.

Requirements for Supplemental Examination: 1 x 1.5 hr(s) paper(s) (corresponding to Mid-Semester Examination and End of Semester Examination) to be taken in Autumn 2020. The mark for Continuous Assessment is carried forward.