Course Catalogue

This programme is aimed for students to learn how to design and develop machine learning and intelligent systems technologies, for the purpose of preparing the students for a range of careers in industry. Intelligent systems are increasingly involved in different areas of human life, for example medicine, space exploration, intelligent agriculture, automated vehicles and more. Machine learning is at the heart of these types of intelligent systems, which are developed using the recent developments in data science and big data across many real world applications. The aim of the programme is to use new knowledge and advance techniques to solve complex machine learning and intelligent systems problems. The students will develop a range of skills including the theory of machine learning, artificial intelligence. They will have an understanding of the principles underlying the development and application of new techniques in the area of machine learning, alongside an awareness of, and ability to analyse the range and scope of algorithms and approaches available, and design, develop and evaluate appropriate algorithms and methods for new problems and applications.

The methods used to enable outcomes to be achieved and demonstrated are as follows: Acquisition of 1 - 10 is through a combination of lectures, tutorials and practical sessions. Throughout the learner is encouraged to undertake independent reading both to supplement and consolidate what is being taught / learnt and to broaden their individual knowledge and understanding of the subject. Knowledge and understanding (Skills 1-6 and 14-19) is assessed via formal examination, individual and team coursework, demonstration of practical work, and a full-scale individual MSc Dissertation. Skills 1 - 7 are taught through lectures and developed through tutorial work throughout the programme. Cognitive skills (Skills 1-2 and 11-16) are partly assessed via formal examinations, but mainly through coursework assessment. The MSc Dissertation allows a student to demonstrate his/her cognitive skills. Practical advanced skills (Skills 10-17) are developed throughout the programme. Key skills are developed throughout the programme in a variety of forms. Specifically through a combination of research related coursework, guided independent study and projects, examinations, group work and presentations. Key skills are assessed as part of coursework, projects, written examinations and presentations.

There are no external placements during the programme. However business skills of project development, management, implementation and presentation are embedded throughout the course. Each student will be allocated to a supervisor who will act as the line-managers for the project. The supervisor will have complementary skill sets in the problem domain and the machine learning domain. Weekly 1 hour meetings of the supervisor and student will monitor progress and provide opportunities for developmental feedback. The aim is to run the projects (7610UPGRAD) in the same fashion as either an academic or industrial project is done externally. As part of the research methods and project modules, the students will be encouraged and assisted to develop a professional on-line presence.