Artificial Intelligence and Machine Learning

Artifical intelligence and machine learning are increasingly important in the rapidly advancing technological landscape. They play a role in many aspects of life. While the scope of applications is diverse and useful, they also come with a host of philosophical and ethical considerations. This unit exposes students to the theory and practical methods associated with the field of artificial intelligence (AI). Students will gain an appreciation for the philosophy, history and applications of artificial intelligence. They will gain an understanding of the functioning of core algorithms within AI, and skills in the application of software tools which implement those algorithms. Areas covered will include knowledge representation, logic and automated reasoning, search, and modelling uncertainty, with a particular emphasis on techniques associated with various areas of machine learning, including unsupervised, supervised and reinforcement learning. Students will also be required to consider the ethics associated with the development and deployment of AI technology within society, and understand the importance of factors such as fairness, safety and explainability.

Topics may include: 1. History and philosophy behind artificial intelligence; current and future applications of artificial intelligence; social implications of AI 2. Logic and search; 3. Knowledge representation, and reasoning - including reasoning with uncertainty; 4. Machine learning - overview, development processes and tools 5. Supervised and semi-supervised learning 6. Dimension reduction, clustering and unsupervised learning; 7. Neural networks and deep learning; deep learning architectures 8. Reinforcement learning;