Artificial Intelligence & Machine Learning - COM00143M
Module summary
This module explores the field of artificial intelligence along with the principal ideas and techniques in three core topic areas: problem solving, knowledge representation and machine learning.
Related modules
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Online Teaching Period 1 2023-24 |
Module aims
This module will explore the field of artificial intelligence and study the principal ideas and techniques in three core topic areas: solving problems by searching, logic, and machine learning. It will help students to develop practical skills in AI problem-solving and to understand the legal and ethical implications of AI for business and society.
Module learning outcomes
After completing the module, students should be able to:
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Critically analyse the principal ideas and techniques of Artificial Intelligence,
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Apply AI search to solve problems that may be represented as states, transitions and goals,
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Design logical systems that are able to represent knowledge and make decisions,
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Apply machine learning techniques to create AI agents that can learn from observed data,
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Critically evaluate the societal impact of AI including legal and ethical issues.
Module content
Topics:
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Artificial intelligence and its application areas.
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Basic AI search algorithms.
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More advanced AI search algorithms.
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Basics of logical systems.
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More advanced topics in propositional logical systems.
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Overview of the three main types of machine learning: supervised, unsupervised, and reinforcement.
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Theory and examples of supervised learning on a range of models.
Indicative assessment
| Task | % of module mark |
|---|---|
| Essay/coursework | 100 |
Special assessment rules
None
Indicative reassessment
| Task | % of module mark |
|---|---|
| Essay/coursework | 100 |
Module feedback
Feedback will be in line with University policy.
Indicative reading
Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (3rd ed. 2009)