AVÊÓƵ

School of Engineering and Informatics (for staff and students)

Intelligent Systems Techniques (802G5)

Intelligent Systems Techniques

Module 802G5

Module details for 2022/23.

15 credits

FHEQ Level 7 (Masters)

Module Outline

This module provides a general introduction to Artificial Intelligence (AI) for postgraduate students. Taking an epistemological perspective, students engage with theories of knowledge and intelligence and get to know related knowledge representation methods and reasoning techniques that are common in AI applications. Alongside the theoretical aspects, students also get hands-on experience in applying and/or implementing the methods and techniques in computer programs.

(Students choosing this module must be able to program, either through successful completion of the Programming through Python module in the autumn semester, or by having equivalent practical experience.
This option is unavailable to those students who previously completed a Computer Science and Artificial Intelligence degree at this University).

Module learning outcomes

Discuss theories of knowledge and related developments in Artificial Intelligence in the context of the historic development of the field.

Demonstrate systematic understanding of several established knowledge representation and reasoning methods such as sentential logic, semantic networks, ontologies, fuzzy systems, and Bayesian networks.

Identify, critically assess, and implement computational techniques that are used in common applications of Artificial Intelligence such as automated reasoning, problem-solving, game-playing, or route-finding.

Demonstrate the ability to engage with academic literature and articulate complex issues related to theories of machine intelligence.

TypeTimingWeighting
Coursework50.00%
Coursework components. Weighted as shown below.
ProjectT2 Week 10 100.00%
Multiple Choice questionsSemester 2 Assessment50.00%
Timing

Submission deadlines may vary for different types of assignment/groups of students.

Weighting

Coursework components (if listed) total 100% of the overall coursework weighting value.

TermMethodDurationWeek pattern
Spring SemesterLaboratory1 hour11111111110
Spring SemesterLecture1 hour22222222222

How to read the week pattern

The numbers indicate the weeks of the term and how many events take place each week.

Dr Chris Thornton

Assess convenor
/profiles/2684

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The University reserves the right to make changes to the contents or methods of delivery of, or to discontinue, merge or combine modules, if such action is reasonably considered necessary by the University. If there are not sufficient student numbers to make a module viable, the University reserves the right to cancel such a module. If the University withdraws or discontinues a module, it will use its reasonable endeavours to provide a suitable alternative module.

School of Engineering and Informatics (for staff and students)

School Office:
School of Engineering and Informatics, AVÊÓƵ, Chichester 1 Room 002, Falmer, Brighton, BN1 9QJ
ei@sussex.ac.uk
T 01273 (67) 8195

School Office opening hours: School Office open Monday – Friday 09:00-15:00, phone lines open Monday-Friday 09:00-17:00
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