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Aims:

In this module students will learn the fundamental concepts and techniques of AI and how they are applied to solve complex real-word problems. The course will equip students with knowledge and tools to tackle new AI problems in different fields.Ìý

• Provide a broad introduction to the different techniques used in AI and their range of applicability.Ìý
• Enable students to propose and design AI solutions to a range of domain specific applications.Ìý
• Enable students to be effective team players in interdisciplinary research groups developing and applying AI systems.

Intended learning outcomes:

On successful completion of the module, a student will be able to:Ìý

1. Demonstrate an understanding of the fundamental concepts in AI.Ìý

2. Demonstrate an understanding of the classical and modern approaches to AI.Ìý

3. Recognize real-word applications where AI modelling can be applied.Ìý

4. Implement and critically evaluate current state-of-the art AI approaches for a range of domain specific applications.Ìý

Indicative content:

The following are indicative of the topics the module will typically cover:

Introduction to AI approaches and the deployment of applications to solve complex real-word problems

Theory and practice of classical AI techniques covering problem representation, search-based AI, knowledge representation and logic-based information technologies, as well as more novel reasoning and planning strategies,

Introduction to hybrids of classical AI with modern machine learning such as symbolic neural networks.

Requisites:

To be eligible to select this module as an optional or elective, a student must be registered on a programme and year of study for which it is formally available.