Core Module Information
Module title: Artificial Intelligence

SCQF level: 09:
SCQF credit value: 20.00
ECTS credit value: 10

Module code: SET09822
Module leader: Ben Paechter
School School of Computing, Engineering and the Built Environment
Subject area group: Computer Science
Prerequisites

Module Code: SET08122
Examples of Equivalent Learning Industry implementation of equivalent algorithms and data structures. Learning involving programming of non-trivial algorithms and data structures.

Description of module content:

The module is partly based on the first three sections of “Artificial Intelligence: A Modern Approach” (3rd edition) by Russell
and Norvig. The indicative content from the book is as follows:
Introduction: What is AI? History of AI and the state of the art.
Agents : An introduction to agents, their behaviors and structure
Searching: Problem solving by searching, heuristics, local search and optimisation and adversarial search
Constraint satisfaction problems: defining and solving CSPs
Logic: Propositional logic, first-order logic, knowledge representation
In addition to this the module will feature introductions to other AI techniques including neural networks, machine learning and nature inspired methods.

Learning Outcomes for module:

LO1: Critically reflect on how AI concepts can underpin problem solving tasks
LO2: Apply the fundamental concepts and origins of artificial intelligence to solve example problems
LO3: Choose, compare and implement AI based solutions to problem solving tasks making use of appropriate software tools and libraries.
LO4: Solve example problems using AI techniques
LO5: Evaluate the effectiveness and appropriateness of specific AI techniques for specific applications

Full Details of Teaching and Assessment

Indicative References and Reading List - URL:
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