COMP3742 Artificial Intelligence - Flinders University

You are viewing an older version of this curriculum item. Select the current year or your commencing year of study from the drop down above. For Pre-2022 Course Rules, use the link located on the right-hand side of the screen.

Alert for students

Flinders City Campus availability offered in 2026.

Overview

This topic will provide a basic understanding of Intelligent Systems and their applications, including a basic understanding and broad overview of Artificial Intelligence and Heuristic Search methodologies, and supervised and unsupervised Machine Learning and Data Mining technologies. The topic provides a balance of theory and practice, with two lectures on theory or philosophy being complemented by seminar-style case studies on specific applications, including guest speakers. Practical work is largely undertaken and assessed in weekly computing laboratory sessions, with a variety of assignments including specification, programming and written tasks. Specific areas to be covered include methodologies and philosophical issues, the relationship of intelligent systems to human intelligence and cognitive science, applications to knowledge engineering, knowledge discovery, language processing, text and data mining, as well as selected topics relating to cognition, perception, visualization and classification/clustering.

Topic availabilities

To view topic availabilities, select an availability from the drop down, towards the top right of the screen.

Tuition pattern

To view tuition patterns, select an availability from the drop down, towards the top right of the screen.

Aims

To be able to specify, consult, deploy and implement intelligent software and systems
To understand and be able to employ Logic Programming, Knowledge Engineering and Knowledge Discovery paradigms and frameworks
To be able assess requirements and select or adapt appropriate methodologies, techniques and tools for the achievement of a task, including through interviewing personnel and reviewing literature
To be able to communicate with non-computing specialists and interdisciplinary specialists in the design of intelligent systems, learning paradigms or data mining applications
To develop an ability to work alone both in a team, including to integrate work and build extensible systems, and to negotiate an ethical solution acceptable to a diverse range of stakeholders

Assessments

To view assessment information, select an availability from the drop down, towards the top right of the screen.

Current students should refer to FLO for detailed assessment information, including due dates. Assessment information is accurate at the time of publishing.

For policy details, visit Assessments

Requisites information

Pre-requisites:

Anti-requisites:

Handbook

Artificial Intelligence

COMP3742