De Montfort University
Intelligent Systems MSc
Leicester, United Kingdom
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LANGUAGES
English
PACE
Full time, Part time
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TUITION FEES
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STUDY FORMAT
Distance Learning, On-Campus
Scholarships
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Introduction
Intelligent Systems MSc
Capitalising on the recent growth in interest in artificial intelligence and intelligent robotics, this course aims to provide you with knowledge of the various models of computational intelligence, skills in the associated computational techniques, an insight into their theoretical basis and the ability to apply these techniques to a wide variety of problems.
There are two similar courses within the department providing you with the flexibility to tailor your learning style and subjects specifically to your requirements. You may also be interested in Intelligent Systems and Robotics MSc which has a robotics focus.
Computational intelligence encompasses the techniques and methods used to tackle problems not well solved by traditional approaches to computing. The four areas of fuzzy logic, neural networks, evolutionary computing and knowledge-based systems encompass much of what is considered to be computational (or artificial) intelligence. There are opportunities to use these techniques in many application areas such as robot control and games development depending on your interests.
Modules include work based on research by the Centre of Computational Intelligence (CCI). With an established international reputation, their work focuses on the use of fuzzy logic, artificial neural networks, evolutionary computing, mobile robotics and biomedical informatics, providing theoretically sound solutions to real-world decision making and prediction problems.
Admissions
Scholarships and Funding
Curriculum
Graduate Careers
Graduates typically follow careers in robotics programming and research, games development, control systems, software engineering, internet businesses, financial services, mobile communications, programming, software engineering and many more. A number of past graduates are now studying for PhDs.
Program Outcome
Past students have published papers with their CCI project supervisors and gone on to PhD study.
Program Tuition Fee
Career Opportunities
Semester 1:
- Computational Intelligence Research Methods details quantitative and qualitative approaches including laboratory evaluation, surveys, case studies and action research.
- Fuzzy Logic considers the various fuzzy paradigms that have become established as computational tools.
- Natural Language Processing focuses on Natural Language Processing (NLP) using Python. It uses NLTK and Pytorch. NLTK is a leading platform for NLP which provides a number of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries. Pytorch provides access to deep learning function which can be applied to NLP problems.
- Mobile Robots discusses the hardware and software architectures used to build mobile robot systems.
Semester 2:
- Computational Intelligence Optimisation (CIO) is a subject that integrates artificial intelligence into algorithms for solving optimisation problems that could not be solved by exact methods. Thus, CIO is the subject that defines and designs metaheuristics, i.e. general purpose algorithms. This makes CIO the subject that tackles optimisation problems in engineering, economics, and applied science
- Artificial Neural Networks and Deep Learning appraises neural network computing from an engineering approach and the use of networks for cognitive modelling.
- Applied Computational Intelligence considers knowledge-based systems; the historical, philosophical and future implications of AI; then focuses on current research and applications in the area
- Intelligent Mobile Robots covers sensing, representing, modelling of the environment, adaptive behaviour and social behaviour of robots. OR
- Data Mining, Techniques and Applications examines the tools and techniques needed to mine the large quantities of data generated in today’s information age. It provides practical experience as well as consideration of research and application areas
Summer:
- Individual Project provides the opportunity to demonstrate skills acquired from the course in a problem solving capacity. This typically involves the analysis, design and implementation of a computer system.
Program delivery
This course is also available in part-time or distance learning study options.
Teaching is normally delivered through lectures, seminars, tutorials, workshops, discussions and e-learning packages. Assessment is via coursework only and will usually involve a combination of individual and group work, presentations, essays, reports and projects.
Distance learning material is delivered primarily through our virtual learning environment. Books, DVDs and other learning materials will be sent to you. We aim to replicate the on-site experience as fully as possible by using electronic discussion groups, encouraging contact with tutors through a variety of mediums.
Flexible study options
- full-time, part time or distance learning study options available; making the course suitable for recent graduates and professionals in work