Courses & Units
Computational Intelligence ENG335
Introduction
The unit covers rule-based expert systems, fuzzy expert systems, frame-based expert systems, artificial neural networks, evolutionary computation, hybrid intelligent systems and knowledge engineering. The aim of this course is to acquaint students with intelligent systems and provide them with a working knowledge for building these systems.
Summary
| Unit name | Computational Intelligence |
|---|---|
| Unit code | ENG335 |
| Credit points | 12.5 |
| College/School | College of Sciences and Engineering School of Engineering |
| Discipline | Engineering |
| Coordinator | Professor Michael Negnevitsky |
| Available as an elective? | Yes |
| Delivered By | University of Tasmania |
| Level | Advanced |
Availability
| Location | Study period | Attendance options | Available to | ||
|---|---|---|---|---|---|
| Hobart | Semester 2 | On-Campus | International | Domestic | |
Key
- On-campus
- Off-Campus
- International students
- Domestic students
Note
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Units are offered in attending mode unless otherwise indicated (that is attendance is required at the campus identified). A unit identified as offered by distance, that is there is no requirement for attendance, is identified with a nominal enrolment campus. A unit offered to both attending students and by distance from the same campus is identified as having both modes of study.
Key Dates
| Study Period | Start date | Census date | WW date | End date |
|---|---|---|---|---|
| Semester 2 | 10/7/2023 | 8/8/2023 | 28/8/2023 | 15/10/2023 |
* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).
Unit census dates currently displaying for 2023 are indicative and subject to change. Finalised census dates for 2023 will be available from the 1st October 2022. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
Learning Outcomes
- Design intelligent systems using neural networks, fuzzy logic and genetic algorithms for solving practical problems.
- Evaluate performance of intelligent systems in solving specific problems in engineering and science.
- Communicate the results of intelligent system designs through writing professional reports.
| Field of Education | Commencing Student Contribution 1,3 | Grandfathered Student Contribution 1,3 | Approved Pathway Course Student Contribution 2,3 | Domestic Full Fee 4 |
|---|---|---|---|---|
| 020119 | $1,037.00 | $1,037.00 | not applicable | $2,938.00 |
1 Please refer to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on eligibility for FEE-HELP.
If you have any questions in relation to the fees, please contact UConnect or more information is available on StudyAssist.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
Requisites
Prerequisites
KME271 or KMA252Teaching
| Teaching Pattern | One 2-hour lecture and one 2-hour computer lab session each week. |
|---|---|
| Assessment | Project based examination (40%)|Assignment 1 (15%)|Assignment 2 (15%)|Assignment 3 (15%)|Assignment 4 (15%) |
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
Required readings will be listed in the unit outline prior to the start of classes. |
Links | Booktopia textbook finder |
|---|
The University reserves the right to amend or remove courses and unit availabilities, as appropriate.