Course summary

The course has several key themes centred on computational thinking, by which we mean the ability to develop and understand algorithmic solutions to problems. This is backed up by the practical skill of programming developed in a variety of relevant languages chosen to complement each other and show the spectrum of techniques and tools available. Students will learn how to apply these to the topic of artificial intelligence, learning about cutting edge techniques such as neural networks, and a range of AI applications. Students will also learn about the underlying architecture that supports computation, both the traditional computer and the new cloud based computation infrastructure which is increasingly prevalent. The course includes a key theme of data science where students work with (potentially very large) datasets, learning the appropriate storage, software and statistical techniques. This will include modern algorithms for machine learning which are revolutionising this field and responsible for much of the recent AI advances. Students will experience how all the previous skills should be combined in the development of an entire product, including the modern tools used in industry such as version control and automated unit testing; the methodologies and design techniques which support such development; and the ethical, social and legal considerations required in such development. Through the study of the above students will also development important degree level transferable skills including both group and individual work, time management, written and verbal presentation to both experts and non-experts, and critical reflection on their own and others work.

Course details