MSc Artificial Intelligence
This new MSc programme in Artifical Intelligence (AI) is highly research-led and incorporates both traditional and state-of-the art aspects of AI and Machine Learning.
The course enables participants to study the fundamentals of all aspects of intelligent algorithms with the freedom to choose options and to specialise where desired. The topics in the course cover a skill base which is in high demand from both the academic research community and a wide range of industrial companies from the biotechnology to finance sectors.
The programme presents a contemporary approach to Artificial Intelligence, covering the fundamental aspects of traditional symbolic and subsymbolic aspects of AI. This provides a solid awareness of the key concepts of the field. In addition to this, through the compulsory Intelligent Algorithms module, students are also exposed to the techniques which form the current basis of Machine Learning and Data Mining. This will give graduates a wide-ranging skill set that supports further study or can be used in application development.
As a result of the leading research being undertaken at Southampton, the course is able to offer a wide range of options which cover state-of-the-art modern techniques which directly reflect research directions in ECS. These include Intelligent Agents, Complexity Science, Computer Vision, Robotics and Machine Learning techniques such as kernel methods and Support Vector Machines.
After completion of the course, you will be prepared for a range of interdisciplinary careers. The demand for scientists with an understanding of Artificial Intelligence and Machine Learning techniques is very high and still growing, both in universities worldwide, but also from the industrial sector, as the data analysis skills covered in the MSc are applicable in a range of areas including bioinformatics, chemoinforamtics, financial services and web applications.
Syllabus
The syllabus for this new course is designed to ensure that all students are exposed to the key topics in all areas.
Optional courses however provide an opportunity for the latest research in cutting edge areas to be incoporated into the course. The options given here will give you a guide to the content and structure of the MSc. Modules are assessed with a mixture of coursework and examinations. Starred modules are optional, and students must take a total of 60 credits per semester.
Semester 1
- COMP3032 Intelligent Algorithms (Compulsory)
- COMP6008 Research Methods in Computing (Compulsory)
- COMP6026 Evolution of Complexity (Compulsory)
- COMP6031 Foundations of Artificial Intelligence (Compulsory)
- COMP3028 Knowledge Technologies (Optional)
- ELEC3012 Robotic Systems (Optional)
Semester 2
- COMP6033 Independent Research Review (Compulsory)
- COMP3005 Computer Vision (Optional)
- COMP3008 Machine Learning (Optional)
- COMP6028 Semantic Web Technologies (Optional)
- COMP6036 Advanced Machine Learning (Optional)
- COMP6041 Computational Finance (Optional)
- ELEC6024 Advanced Computer Vision (Optional)
- ELEC6087 Biologically-Inspired Robotics (A) (Optional)
Semester 3/Summer
- COMP6029 MSc Project and Dissertation (Compulsory)
Summer Project
The MSc involves a substantial individual research project lasting three months and worth 60 credits. This give you an opportunity to explore on of the areas covered in the course in depth, with the benefit of supervision by a supervisor who is research active in that area. It is often the case that students are involved directly with currently running research projects within the research group, thus providing an opportunity to experience the culture of research and give you valuable experience of taking part in a range of research activities.
This course is based jointly between the ISIS and IAM research groups, with also involvement from the SENSe research group.
Admissions Tutors
Dr Craig Saunders