Studying online
There are now 2 possible online modes for units:
Units with modes Online timetabled and Online flexible are available for any student to self-enrol and study online.
Click on an offering mode for more details.
Unit Overview
- Description
This unit focuses on deep learning concepts and their applications. Assuming basic machine learning knowledge, and experience in related programming frameworks, it will delve deeper into the building blocks of modern deep learning systems and their specialised applications in processing structured and unstructured data. The unit covers fundamental neural architectures, including feedforward neural networks, convolutional neural networks, recurrent neural networks, gated recurrent units, long-short term memory and autoencoders, with practical examples on applications to vision and language data. These will build foundational understandings to advanced topics in variational autoencoders, Generative Adversarial Networks (GANs), transformers, deep reinforcement learning, and policy gradient methods.
- Credit
- 6 points
- Offering
(see Timetable) Availability Location Mode Semester 2 UWA (Perth) Face to face - Outcomes
Students are able to (1) demonstrate efficacy in applying deep neural networks on structured and unstructured data; (2) demonstrate understanding of autoencoders for semi-supervised learning and dimensionality reduction; (3) apply sequence processing methods to time-series data; (4) apply generative models for data generation; (5) apply generative adversarial networks to learn data distribution; and (6) demonstrate understanding of deep reinforcement learning.
- Assessment
Indicative assessments in this unit are as follows: (1) mid-semester test; (2) final examination; and (3) practical projects. Further information is available in the unit outline.
Student may be offered supplementary assessment in this unit if they meet the eligibility criteria.
- Unit Coordinator(s)
- Associate Professor Du Huynh
- Unit rules
- Prerequisites
- Successful completion ofCITS5508 Machine Learning
- Contact hours
- lectures: 2 hours per week
laboratories: 2 hours per week.
- The availability of units in Semester 1, 2, etc. was correct at the time of publication but may be subject to change.
- All students are responsible for identifying when they need assistance to improve their academic learning, research, English language and numeracy skills; seeking out the services and resources available to help them; and applying what they learn. Students are encouraged to register for free online support through GETSmart; to help themselves to the extensive range of resources on UWA's STUDYSmarter website; and to participate in WRITESmart and (ma+hs)Smart drop-ins and workshops.
- Visit the Essential Textbooks website to see if any textbooks are required for this Unit. The website is updated regularly so content may change. Students are recommended to purchase Essential Textbooks, but a limited number of copies of all Essential Textbooks are held in the Library in print, and as an ebook where possible. Recommended readings for the unit can be accessed in Unit Readings directly through the Learning Management System (LMS).
- Contact hours provide an indication of the type and extent of in-class activities this unit may contain. The total amount of student work (including contact hours, assessment time, and self-study) will approximate 150 hours per 6 credit points.
Face to face
Predominantly face-to-face. On campus attendance required to complete this unit. May have accompanying resources online.
Online flexible
100% Online Unit. NO campus face-to-face attendance is required to complete this unit. All study requirements are online only. Unit is asynchronous delivery, with NO requirement for students to participate online at specific times.
Online timetabled
100% Online Unit. NO campus face-to-face attendance is required to complete this unit. All study requirements are online only. Unit includes some synchronous components, with a requirement for students to participate online at specific times.
Online Restricted
Not available for self-enrolment. Students access this mode by contacting their student office through AskUWA. 100% Online Unit.
NO campus face-to-face attendance. All study and assessment requirements are online only. Unit includes some timetabled activities, with a requirement for students to participate online at specific times. In exceptional cases (noted in the Handbook) students may be required to participate in face-to-face laboratory classes when a return to UWA’s Crawley campus becomes possible in order to be awarded a final grade.
External
No attendance or regular contact is required, and all study requirements are completed either via correspondence and/or online submission.
Off-campus
Regular attendance is not required, but student attends the institution face to face on an agreed schedule for purposes of supervision and/or instruction.
Multi-mode
Multiple modes of delivery. Unit includes a mix of online and on-campus study requirements. On campus attendance for some activities is required to complete this unit.