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Artificial Intelligence Techniques PG (6685.5)

Level: Postgraduate Level
Credit Points: 3
HECS Bands: 2
Faculty: Faculty of Science and Technology
Discipline: Academic Program Area - Technology

Availability

Possible changes to your unit's learning activities and assessment items

For the remainder of 2020, resulting from Australian Government's directives requiring physical distancing and restrictions on movement because of the COVID-19 pandemic, any exams that are required for assessment in a unit will be online exams. Online exams may also use online proctoring to help assure the academic integrity of those exams. Please contact your unit convener with any questions.

While the University has made efforts to ensure that Unit Outlines reflect a unit’s learning activities and assessment items, any changes to Australian Government directives because of the COVID-19 pandemic may require changes to these during the semester to ensure the safety and well being of students and staff. These changes will not be updated in the published unit outline, but will be communicated to you via your unit’s UCLearn(Canvas) teaching site. Any changes made will continue to meet the unit’s learning outcomes, as described in the Unit Outline.

Syllabus

This unit looks at those techniques and concepts implemented as software that carries out actions which are normally thought of as requiring intelligence when carried out by humans. Topics are selected from knowledge representation, heuristic search and problem reduction, AI algorithms, natural language processing, decision support systems, expert systems, computer assisted instruction, speech understanding, vision, theorem proving, pattern recognition, robotics, games, data mining, scheduling, constraint processing and optimisation.

Learning Outcomes

  1. From this unit, the students will be able to define and appraise the major areas of AI research and use. They will be able to write simple programs to demonstrate aspects of AI using a suitable programming language.

Contact Hours

Up to 39 hours per semester.

Prerequisites

Must have passed 11521 Programming for Data Science G OR 8995 Software Technology 1 G

Corequisites

None.

Assumed Knowledge

None.

Incompatible Units

None.

Equivalent Units

None.


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