2018/19 Taught Postgraduate Programme Catalogue
MSc Advanced Computer Science (Intelligent Systems)
Programme code: | MSC-ACS/I-FT | UCAS code: | |
---|---|---|---|
Duration: | 12 Months | Method of Attendance: | Full Time |
Programme manager: | Dr Vania Dimitrova | Contact address: | V.G.Dimitrova@leeds.ac.uk |
Total credits: 180
Entry requirements:
A minimum UK Upper Second Class Honours (2.1) degree or equivalent in computing or a scientific subject with significant computing component;
- A pass at GCSE level English Language (grade C or above);
- International students must have an English language qualification at a suitable level: IELTS 6.5 or equivalent.
School/Unit responsible for the parenting of students and programme:
School of Computing
Examination board through which the programme will be considered:
School of Computing
Relevant QAA Subject Benchmark Groups:
Computing
Programme specification:
On completion of the programme students should be a able to demonstrate:
- a systematic understanding of the theory and practice of designing and implementing computer systems
- proficiency in the technical and programming skills required to design and implement computer systems;
- a thorough knowledge and skills base in a number of advanced topics within the domain of computer science;
- an in-depth knowledge of the essential principles and practices used in the effective design, implementation and usability of Intelligent Systems;
- the ability to apply these principles and practices to tackle a significant problem within the main project;
- an in-depth understanding of an area of specialisation, gained during the main project;
- be confident in applying the research methodology adopted for the main project on new problems;
- be prepared for further study either in the context of professional development or through further engagement in higher education.
The programme will:
- situate the study of Intelligent Systems within the general context of computational modelling and complex systems.
- give a broad perspective on Intelligent systems, covering evolutionary models, statistical and symbolic machine learning algorithms, qualitative reasoning, image processing, language understanding, and bio-computation.
-be rooted in established research strengths of the School and will offer the opportunity for students to work as integral members of our research groups during their main project.
- prepare graduates for graduate careers in the IT industry and other contexts or for further study either in the context of continuing professional development or through further engagement in higher education.
Year1 - View timetable
[Learning Outcomes, Transferable (Key) Skills, Assessment]
Compulsory modules:
Candidates will be required to study the following compulsory modules:
COMP5200M | MSc Project | 60 credits | 1 Jan to 30 Sep | |
COMP5400M | Bio-Inspired Computing | 15 credits | Semester 2 (Jan to Jun) | |
COMP5450M | Knowledge Representation and Reasoning | 15 credits | Semester 1 (Sep to Jan) | |
COMP5870M | Image Analysis | 15 credits | Semester 2 (Jan to Jun) |
Optional modules:
Candidates will be required to study 75 credits from the following lists of optional modules:
COMP5111M | Big Data Systems | 15 credits | Semester 2 (Jan to Jun) | |
COMP5122M | Data Science | 15 credits | Semester 1 (Sep to Jan) | |
COMP5811M | Parallel and Concurrent Programming | 15 credits | Semester 1 (Sep to Jan) | |
COMP5850M | Cloud Computing | 15 credits | Semester 2 (Jan to Jun) | |
COMP5860M | Semantic Technologies and Applications | 15 credits | Semester 2 (Jan to Jun) | |
COMP5911M | Advanced Software Engineering | 15 credits | Semester 1 (Sep to Jan) | |
COMP5920M | Scheduling | 15 credits | Semester 2 (Jan to Jun) | |
COMP5930M | Scientific Computation | 15 credits | Semester 1 (Sep to Jan) | |
COMP5940M | Graph Theory: Structure and Algorithms | 15 credits | Semester 2 (Jan to Jun) |
Students may study no more than 30 credits from this list:
COMP3211 | Distributed Systems | 10 credits | Semester 1 (Sep to Jan) | |
COMP3222 | Mobile Application Development | 10 credits | Semester 2 (Jan to Jun) | |
COMP3611 | Machine Learning | 10 credits | Semester 1 (Sep to Jan) | |
COMP3631 | Intelligent Systems and Robotics | 20 credits | Semester 1 (Sep to Jan) | |
COMP3771 | User Adaptive Intelligent Systems | 10 credits | Semester 2 (Jan to Jun) | |
COMP3776 | Data Mining and Text Analytics | 10 credits | Not running in 201819 | |
COMP3910 | Combinatorial Optimisation | 10 credits | Semester 2 (Jan to Jun) | |
COMP3940 | Graph Algorithms and Complexity Theory | 10 credits | Semester 1 (Sep to Jan) |
Last updated: 12/07/2019
Browse Other Catalogues
- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue
Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD