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.
Pre-requisite modules
Co-requisite modules
- None
Prohibited combinations
- None
Occurrence | Teaching period |
---|---|
A | Online Teaching Period 3 2024-25 |
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.
After completing the module, students should be able to:
Critically analyse the principal ideas and techniques of Artificial Intelligence,
Apply AI search to solve problems that may be represented as states, transitions and goals,
Design logical systems that are able to represent knowledge and make decisions,
Apply machine learning techniques to create AI agents that can learn from observed data,
Critically evaluate the societal impact of AI including legal and ethical issues.
Topics:
Artificial intelligence and its application areas.
Basic AI search algorithms.
More advanced AI search algorithms.
Basics of logical systems.
More advanced topics in propositional logical systems.
Overview of the three main types of machine learning: supervised, unsupervised, and reinforcement.
Theory and examples of supervised learning on a range of models.
Task | Length | % of module mark |
---|---|---|
Essay/coursework Coursework |
N/A | 100 |
None
Task | Length | % of module mark |
---|---|---|
Essay/coursework Coursework |
N/A | 100 |
Feedback will be in line with University policy.
Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (3rd ed. 2009)