SIG744 - Deep Learning
| Year: | 2026 unit information |
|---|---|
| Enrolment modes: | Trimester 2: Great Learning |
| Credit point(s): | 1 |
| EFTSL value: | 0.125 |
| Prerequisite: | Nil |
| Corequisite: | Must be enrolled in S732 Master of Applied Artificial Intelligence (Global) |
| Incompatible with: | SIT319, SIT744 |
| Study commitment: | Students will on average spend 150 hours over the trimester undertaking the teaching, learning and assessment activities for this unit. This will include educator guided online learning activities within the unit site. |
| Scheduled learning activities - online: | Online independent and collaborative learning including optional scheduled activities as detailed via the Great Learning platform. |
| Note: | This unit is part of the Master of Applied Artificial Intelligence (Global) program and is restricted to online international students who reside outside Australia. |
Content
Deep learning is a disruptive technology for data science and artificial intelligence. This unit allows students to develop practical knowledge of deep learning and associated applications. Learning activities will focus on understanding deep learning theories, constructing deep learning models for handling structured and unstructured data, such as images, videos, and texts. Concepts such as computational graphs and representation learning that form core knowledge in this unit will be introduced. Students will also learn about deep learning techniques for data analytics such as convolutional networks, recurrent networks, and neural embedding methods which are being widely adopted in industries.