Total Credits: 10
Level: Level 1
Target Students: Qualifying year undergraduate students in the School of Computer Science. This module is part of the AI, Modelling and Optimisation theme in the School of Computer Science.
|Spring||Assessed by end of Spring Semester|
Prerequisites: Students who have previously taken G51PRG cannot take this module.
Summary of Content: Through a two hour lecture once a week, this module gives you a broad overview of the fundamental theories and techniques of Artificial Intelligence (AI). You’ll explore how computers can produce intelligent behaviour, and will consider topics such as the history of AI, search techniques, data mining, machine learning, game playing techniques, neural networks, philosophical issues, and knowledge representation and reasoning.
Method and Frequency of Class:
|Activity||Number Of Weeks||Number of sessions||Duration of a session|
|Lecture||10 weeks||1 per week||2 hours|
|Practical||10 weeks||1 per week||2 hours|
|Practical||12 weeks||1 per week||2 hours|
Method of Assessment:
|Exam 1||75||1.5 hr written examination|
|Coursework 1||25||Search and Machine Learning|
Mr S Ho
Education Aims: To introduce students to Artificial Intelligence, its history and some key AI techniques.
Learning Outcomes: Knowledge and Understanding: Knowledge of key AI techniques. Intellectual Skills: The ability to think independently while giving due weight to the arguments of others. The ability to analyse algorithms. Professional Skills: The ability to evaluate available AI techniques and select those appropriate to a given problem. Transferable Skills: The ability to solve problems and communicate effectively in writing.
Offering School: School of Computer Science
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