Module catalogue

CU6051 - Artificial Intelligence (2025/26)

Module specification

Module approved to run in 2025/26

Module title

Artificial Intelligence

Module level

Honours (06)

Credit rating for module

School

School of Computing and Digital Media

Total study hours

150

45 hours	Scheduled learning & teaching activities
105 hours	Guided independent study

Assessment components

Type	Weighting	Qualifying mark	Description
Coursework	25%		Documentation
Coursework	75%		Artefact + documentation

Running in 2025/26

(Please note that module timeslots are subject to change)

No instances running in the year

Module summary

This module provides an introduction to the field of Artificial Intelligence, from its historical context to its current state. Students will research an aspect of AI and work in teams to design an intelligent system and develop a simple prototype.

The module aims to

· to build students’ knowledge and understanding of AI and its range of applications;

· to enable students to use their skills and knowledge to design a contemporary intelligent system;

· to develop students’ critical faculties with respect to the ethics and the issues surrounding AI;

· to build skills in software engineering and prototype development

Syllabus

Agents and environments

Reflex, goal-based agents

State machines

Pathfinding

Knowledge-based systems

Adversarial search

Multi-agent environments

Markov models, uncertainty

Natural Language Processing

high-performance computing (HPC)

Robotics

Human augmentation

Unity tutorials – basics, navigation meshes, decision trees, flocking and steering behaviours

Balance of independent study and scheduled teaching activity

Students will have the opportunity to engage in discussions and take part in workshops on different topics.

Combination of

· Lectures for defining concepts, describing methods and discussing alternatives

· Workshops for demonstrating software tools and platforms, configuring working

environments, prototyping solutions, discussing alternatives and acquiring hands-on experience

· Individual coursework for reporting technological research and technical

solutions, comparing design alternatives and personal reflection

· Blended learning through the use of Virtual Learning Environments (VLE) for

setting problem scenarios, providing prepared solutions, submitting assessment

materials and obtaining feedback

· In-class demonstration of AI solutions for evaluation and reflection of

individual practice

Learning outcomes

Upon successful completion of this module students will be able to:

LO1- Gain knowledge and understanding of artificial intelligence

LO2 - Be able to work effectively in teams to design an intelligent system

LO3 - Demonstrate ability to communicate effectively on the topic of AI

LO4 – Be able to develop and evaluate a simple AI prototype from a brief

Bibliography

https://rl.talis.com/3/londonmet/lists/270F286A-5F5C-A791-6A4F-7EB67D8389CC.html?lang=en-GB&login=1

CORE TEXT: