New MSc in Artificial Intelligence
The MSc which will be offered by the University of Southampton's School of Electronics & Computer Science (ECS) in October this year, builds on the School's flourishing MSc programme which this year attracted a record 145 students. The School has also just witnessed its largest Computer Science undergraduate intake since the dot-com crash.
The new MSc in Artificial Intelligence is research-led and incorporates both traditional and state-of-the art aspects of AI and Machine Learning, opening the path to many different subject areas and technologies.
‘AI and Machine Learning are becoming ever more prevalent in our society,’ said Dr Craig Saunders, Joint Course Leader. According to Dr Saunders, millions of people are already familiar with some of the scenarios where AI technologies are already employed, such as: web search, weather prediction, financial forecasting and 'personal recommended items' on shopping and music websites.
‘There is also much potential for these techniques in bio-informatics and chemo-informatics where proteomics and genomics are benefiting from novel algorithms; as well as spam filtering, opponent AI in modern computer games, and of course, robotics.’ said Dr Saunders.
The course will enable participants to study the fundamentals of all aspects of intelligent algorithms with the freedom to choose options and specialise where desired. Topics in the course cover a skill base which is in very high demand from the academic research community as well as a wide range of industrial companies covering sectors from biotechnology to finance.
‘The school has been very active in this area and conducting world-class research for some time and has many researchers working in various elements of Artificial Intelligence, including Intelligent Agents, Machine Learning, Game Theory, Evolutionary Algorithms, Complexity Science, Biometrics and Machine Vision among others,’ said Dr Saunders. ‘We have had a strong AI component to our undergraduate degree for many years, with many students electing to focus on this aspect in their third year project, including the recent success of Richard Jones and LastFM who used collaborative filtering techniques to recommend music to listeners.’
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