COMP8920 Neural Networks, Deep Learning and Bio-inspired Computing
Not offered in 20246 units8000-level
A neural network is a computational paradigm based on insights from the brain, consisting of many simple processing elements together producing complex computations. Deep learning uses many neural network layers for advanced feature recognition and prediction. Bio-inspired Computing is the combination of computational intelligence and collective intelligence. These computational methods are used to solve complex problems, and modeled after design principles encountered in natural / biological systems, and tend to be adaptive, reactive, and distributed. The goal of bio-inspired computing is to produce computational tools with enhanced robustness, scalability, flexibility and which can interface more effectively with humans. This course introduces the fundamental topics in bio-inspired computing, and build proficiency in the application of various algorithms in real-world problems. The course will also cover applications focused particularly on highly sophisticated interaction with users.
- 2024not offered
- 2025not listed
- 2026not listed
- 2027not listed
Prerequisites in 2024
The handbook's wording is ambiguous; this is a person's reading of it
Why it's read this way: The bracket holds the MADAN pathway, and its "and" binds the program to the course list.
The handbook's original wording (2024)
To enrol in this course you must have either completed COMP6670 OR (be enrolled in the Master of Applied Data Analytics and have completed 6 units of either COMP6710 or COMP6730 or COMP7230 ).
What it leads to in 2024
No course names COMP8920 in its 2024 prerequisites.