Fundamentals of Artificial Intelligence - COMP5003

Looking for a different module?

Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2026 to 2027
Canterbury
Spring Term 5 20 (10) Palaniappan Ramaswamy checkmark-circle

Overview

The omnipresence of Artificial Intelligence (AI) is undeniable; it is not merely a futuristic concept but a current reality that permeates almost every facet of our lives. As we witness AI's pervasive influence, it becomes evident that it is destined to be an integral part of our everyday existence.

In this dynamic module, you will be introduced to the essential concepts of AI, setting the stage for a profound exploration into more advanced realms such as machine learning and bio-inspired computations. Hands-on coding exercises, utilising a programming AI tool, enriches your theoretical foundation and further solidifies your understanding.

Emphasis on real-world considerations ensures that you emerge well-prepared to tackle more advanced modules later as you will not only possess a foundational understanding of AI but also wield practical expertise essential for active participation in AI development.

Details

Contact hours

Total Contact Hours (Lectures, Classes) 38, Independent Study 112 ,Assessment Preparation 50.

Availability

Spring

Method of assessment

Weekly online tests worth 25%.
Weekly mini practical exercises worth 25%.
Examination worth 50%.

Reassessment Method: Like-for-like Including composite form of reassessment for failed coursework components – mini-practical exercise, and Examination.

Indicative reading

Learning outcomes

On successfully completing the module, students will be able to:

1. Describe motivations behind the design of intelligent machines and their implications.

2. Demonstrate critical understanding of various state-space search algorithms and their strengths and limitations.

3. Understand, implement and critically evaluate machine learning approaches.

4. Describe and apply principles of biologically-inspired algorithms.

5. Apply and evaluate intelligent techniques for real-world scenarios.

Notes

  1. Credit level 5. Intermediate level module usually taken in Stage 2 of an undergraduate degree.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
Back to top

University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. However, courses, services and other matters may be subject to change. Please read our full disclaimer.