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Unit information: Introduction to Artificial Intelligence in 2021/22

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 Introduction to Artificial Intelligence
Unit code EMATM0044
Credit points 10
Level of study M/7
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Dr. Lewis
Open unit status Not open

Basic competency in Python or Matlab at the level of EMAT10007 or EMAT20920



School/department School of Engineering Mathematics and Technology
Faculty Faculty of Engineering

Description including Unit Aims

This unit will provide a broad introduction to AI for MSc students in SCEEM. It will provide an overview of the most established AI and Machine Learning approaches and paradigms and give students the opportunity to implement AI algorithms and use relevant software tools. Areas covered will included supervised learning (classification and regression, e.g. neural networks), unsupervised learning (clustering), probabilistic methods (e.g. Bayesian networks and Markov decision processes), genetic algorithms, and multi-agent systems.

Intended Learning Outcomes

Upon successful completion of the course, students will be able to:

  1. Be able to explain basic concepts and assumptions underpinning key AI algorithms
  2. Rigorously compare the performance of competing methods.
  3. Implement AI algorithms in a suitable programming language and toolboxes.
  4. Apply machine learning to analyse data.
  5. Modelling the behaviour of autonomous systems.

Teaching Information

Teaching will be delivered through a combination of synchronous and asynchronous sessions, including lectures, practical activities supported by drop-in sessions or online computer laboratories and problem sheets.

Assessment Information

2 Summative Assessments, 50% Coursework + 50% Exam.


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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.