CSU33061 – Artificial Intelligence I

Module Code	CSU33061
Module Name	Artificial Intelligence I
ECTS Weighting [1]	5 ECTS
Semester Taught	Semester 2
Module Coordinator/s	Tim Fernando

Module Learning Outcomes

On successful completion of this module, students will be able to:

Describe the basic aims and achievements of artificial intelligence, as well as the challenges facing it;
Assess notions of computability as they relate to artificial intelligence;
Reason about the suitability of and trade-offs between basic search strategies;
Design simple knowledge representation systems for various knowledge intensive problems;
Appreciate the possibilities opened up by probabilistic reasoning.

Module Content

An introduction to Artificial Intelligence covering basic topics: search, knowledge representation and probabilistic reasoning (Markov Decision Processes, Bayes nets, Markov nets and neural nets).

Teaching and Learning Methods

Lectures, laboratories, tutorials.

Assessment Details

Assessment Component	Brief Description	Learning Outcomes Addressed	% of Total	Week Set	Week Due
Examination	2 hour In-person Examination	LO1, LO2, LO3, LO4, LO5	80%
Coursework	2 Problem Sets	LO1, LO2, LO3, LO4, LO5	20%	Week 4,8 (approximately)	The following week

Reassessment Details

Real-time examination (2 hours, 100%),

Contact Hours and Indicative Student Workload

Contact Hours (scheduled hours per student over full module), broken down by:	44 hours
Lecture	22 hours
Laboratory	11 hours
Tutorial or seminar	11 hours
Other	0 hours
Independent Study (outside scheduled contact hours), broken down by:	72 hours
Preparation for classes and review of material (including preparation for examination, if applicable)	36 hours
Completion of assessments (including examination, if applicable)	36 hours
Total Hours	116 hours

Module Pre-requisites

Prerequisite modules: CSU34011

Other/alternative non-module prerequisites:

Module Co-requisites

N/A

Module Website

Blackboard