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Months of entry
The human brain is a hugely complex machine that is able to perform tasks that are vastly beyond current capabilities of artificial systems. Understanding the brain has always been a source of inspiration for developing artificially intelligent agents and has led to some of the defining moments in the history of AI. At the same time, theoretical insights from artificial intelligence provide new ways to understand and probe neural information processing in biological systems.
The specialisation in Computation in Neural and Artificial Systems will involve both theoretical and practical components. The practical component will addresses how models based on neural information processing can be used to develop artificial systems, probing of human information processing in closed-loop online settings, as well as the development of new machine learning techniques to better understand human brain function.
The theoretical component will address various ways of modeling and understanding cognitive processing in humans. These range from abstract mathematical models of learning that are derived from Bayesian statistics, complexity theory and optimal control theory to neural information processing systems such as deep neural networks that simulate particular cognitive functions in a biologically inspired manner.
*This is an specialisation of the Master's in Artificial Intelligence
Fees and funding
Qualification and course duration
MSc by research
Course contact details
- Admission Office