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Artificial Intelligence for Mechatronics (MCEN90048)
Graduate courseworkPoints: 12.5On Campus (Parkville)
For information about the University’s phased return to campus and in-person activity in Winter and Semester 2, please refer to the on-campus subjects page.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Please refer to the LMS for up-to-date subject information, including assessment and participation requirements, for subjects being offered in 2020.
Overview
Availability | Semester 1 |
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Fees | Look up fees |
Upon completion, students are expected to gain an overview of a major branch of artificial intelligence known as computational intelligence or soft computing, and their applicability to mechatronic systems. Students are expected to practice some of the methods they learn on real and synthetic data and appreciate the strengths and limits of the approaches they learn.
A variety of topics in computational intelligence are expected to be covered, with selections to be made from 1) neural networks including generative networks, deep neural networks and convolution neural networks, 2) learning methods including unsupervised learning, reinforcement learning and semi-supervised learning, 3) appreciation of other Computational Intelligence methods: fuzzy systems and evolutionary algorithms and 4) an introduction to stochastic dynamic programming and its relationship to AI. Mechatronic applications in broader terms and case studies from other relevant areas of engineering will be discussed.
Intended learning outcomes
At the conclusion of this subject students should be able to:
- Understand the concepts of Neural Networks and various types of learning algorithms
- Understand the concepts of artificial intelligence approaches to optimization
- Choose the best artificial intelligence approaches for various classes of real problems including engineering design and data centric modelling
- Implement and analyze the capability and limitations of artificial intelligence in engineering applications
Generic skills
- Application of knowledge of basic science and engineering fundamentals
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
ELEN90055 Control Systems
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 3 November 2022
Assessment
Due to the impact of COVID-19, assessment may differ from that published in the Handbook. Students are reminded to check the subject assessment requirements published in the subject outline on the LMS
Description | Timing | Percentage |
---|---|---|
One project assignment with 3 components - component 1 due week 4 (5%), component 2 due week 8 (5%), component 3 due week 11 (20%).
| Throughout the semester | 30% |
End of semester exam - closed book
| End of semester | 60% |
Pre-lecture quizzes (4 throughout semester)
| Throughout the semester | 10% |
Last updated: 3 November 2022
Dates & times
- Semester 1
Principal coordinator Saman Halgamuge Mode of delivery On Campus (Parkville) Contact hours 36 hours comprising two 1 hour lectures and a 1 hour workshop each week. Total time commitment 200 hours Teaching period 2 March 2020 to 7 June 2020 Last self-enrol date 13 March 2020 Census date 30 April 2020 Last date to withdraw without fail 5 June 2020 Assessment period ends 3 July 2020
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 3 November 2022