Advanced Methods in Bio-inspired AI (983G5)

15 credits, Level 7 (Masters)

Autumn teaching

On this module, you'll develop your understanding of recent bio-inspired approaches to AI, including their relevance to neuromorphic computing. The benefits, limitations and open challenges of bio-inspired approaches will be discussed.

Key topics include:

• spiking neural networks including gradient descent with surrogate gradients and exact gradient algorithms
• fundamentals of neuromorphic computing approaches
• bio-plausible local learning and inference strategies, their benefits and limitations
• bio-inspired approaches to unsupervised learning.

These topics will be introduced in the context of recent research publications. 

Contact hours and workload

This module is approximately 150 hours of work. This breaks down into about 44 hours of contact time and about 106 hours of independent study. The University may make minor variations to the contact hours for operational reasons, including timetabling requirements.

We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2024/25. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum.

We’ll make sure to let you know of any material changes to modules at the earliest opportunity.