12 monthsProgramme duration
SepStarting Month
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
This MSc will teach you the theoretical aspects of AI and provide the practical skills needed to work with big data sets for solving a wide range of real-world problems. You’ll gain the expertise necessary to develop and work with AI systems, across a wide range of disciplines.
Artificial Intelligence (AI) impacts many aspects of our lives, from life-style choices to healthcare, advanced engineering and self-driving vehicles. The study of the foundations of AI is multi-disciplinary, incorporating aspects of computer science, mathematics/statistics, psychology and in terms of its impact and application, natural, physical and social sciences.
This course is designed for students with a numerate background (for example, an undergraduate degree in mathematics, economics, engineering, physics or chemistry) as well as graduates already working in industry.
During the course, you’ll explore a range of topics, covering both theoretical and practical aspects of AI.
The programme consists of lectures, practical work and an individual dissertation project, in which you undertake a significant AI-themed research project under the supervision of a member of staff.
An essential part of AI is ‘learning from data’ and the programme will include training on software development for the analysis of data, or on robust data analysis methodologies to cope with missing or corrupted data. At the end of the course, graduates will be prepared for work in a wide variety of jobs in which comprehensive knowledge and understanding of AI is required.
Accreditation
This course is accredited by the British Computer Society (BCS). The course partially meets the requirements for Chartered Information Technology Professional (CITP) and partially meets the requirements for Chartered Engineer (CEng).
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
This MSc will teach you the theoretical aspects of AI and provide the practical skills needed to work with big data sets for solving a wide range of real-world problems. You’ll gain the expertise necessary to develop and work with AI systems, across a wide range of disciplines.
Artificial Intelligence (AI) impacts many aspects of our lives, from life-style choices to healthcare, advanced engineering and self-driving vehicles. The study of the foundations of AI is multi-disciplinary, incorporating aspects of computer science, mathematics/statistics, psychology and in terms of its impact and application, natural, physical and social sciences.
This course is designed for students with a numerate background (for example, an undergraduate degree in mathematics, economics, engineering, physics or chemistry) as well as graduates already working in industry.
During the course, you’ll explore a range of topics, covering both theoretical and practical aspects of AI.
The programme consists of lectures, practical work and an individual dissertation project, in which you undertake a significant AI-themed research project under the supervision of a member of staff.
An essential part of AI is ‘learning from data’ and the programme will include training on software development for the analysis of data, or on robust data analysis methodologies to cope with missing or corrupted data. At the end of the course, graduates will be prepared for work in a wide variety of jobs in which comprehensive knowledge and understanding of AI is required.
Accreditation
This course is accredited by the British Computer Society (BCS). The course partially meets the requirements for Chartered Information Technology Professional (CITP) and partially meets the requirements for Chartered Engineer (CEng).
Admission Requirements
Minimum 2:1 undergraduate honours degree in a relevant subject.
Please see our website for the full list of accepted subjects.
English language requirements: IELTS 6.5 (with 6 in each component) or University equivalent.
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