Course overview
This course will provide students with an advanced understanding of deep learning applications by exploring the theory and practical implementation of deep neural networks.
Course learning outcomes
- Explain the fundamental concepts and theories of deep learning, including the architecture and functioning of neural networks
- Design, implement, and train convolutional neural networks (CNNs) for image processing and classification tasks
- Develop recurrent neural networks (RNNs) and their variants (LSTM, GRU) for sequential data processing and natural language processing applications
- Apply advanced deep learning techniques such as transfer learning, generative adversarial networks (GANs), and reinforcement learning to enhance model performance
- Evaluate the performance of deep learning models using appropriate metrics and techniques, and optimise models for improved accuracy and efficiency
- Integrate and apply deep learning knowledge and skills in a comprehensive capstone project, demonstrating the ability to solve complex real-world problems
Availability
Class details
Adelaide City Campus East
Class number 25525
Section FR01
Size 160
Available 160
Class number 29063
Section WS01
Size 30
Available 30
Class number 29062
Section WS02
Size 30
Available 30
Class number 29061
Section WS03
Size 30
Available 30
Class number 29060
Section WS04
Size 30
Available 30
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The Student Contribution amount displayed below is for students commencing a new program from 2021 onwards. If you are continuing in a program you commenced prior to 1 January 2021, or are commencing an Honours degree relating to an undergraduate degree you commenced prior to 1 January 2021, you may be charged a different Student Contribution amount from the amount displayed below. Please check the Student Contribution bands for continuing students here. If you are an international student, or a domestic student studying in a full fee paying place, and are continuing study that you commenced in 2025 or earlier, your fees will be available here before enrolments open for 2026.