COMP8536 Advanced Topics in Deep Learning for Computer Vision
Not offered in 20266 units8000-level
The course covers the theory and practice of deep learning with a focus on applications in computer vision. Students will learn the foundational mathematics behind deep learning and explore topics such as multi-layer perceptrons (MLPs), back-propagation and automatic differentiation, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and Transformers. These techniques play a crucial role in modern AI systems, including image and video understanding, natural language processing, generative AI, and robotics. The various practical assessments will enhance student's understanding and intuition of deep learning and its application in computer vision.
- 2024S2
- 2025not offered
- 2026not offered
- 2027not offered
Prerequisites in 2026
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The handbook's original wording (2024–2027)
To enrol in this course you must be studying Master of Engineering or Master of Machine Learning and Computer Vision or Master of Computing (Advanced). Students must have completed either COMP6710 or COMP6730 or equivalent.
What it leads to in 2026
No course names COMP8536 in its 2026 prerequisites.