This course offers both a broad perspective on intelligent systems, covering evolutionary models, statistical and symbolic machine learning algorithms, qualitative reasoning, image processing, language understanding and bio-computation with a thorough knowledge of the essential principles and practices used in the effective design, implementation and usability of intelligent
The course is rooted in the established research strengths of the School and will offer you the opportunity to gain an in-depth understanding of an area of specialisation during the main research project where you will work as integral members of our research groups. You will apply your knowledge and skills to tackle a significant problem, which will prepare you for a graduate career in the IT industry or for further study.
The adoption of intelligent systems is increasing rapidly and varies from software agents used in networking systems to embedded systems in robots and unmanned vehicles to provide systems that can work unsupervised or to enhance human activities.
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The tables below show the modules that you will study if you commence your studies in September 2013. This information is taken from the University Programme Catalogue, which is a tool designed for current students to select modules.
If you are looking to start your studies in September 2014 a list of modules is available in the 2014 brochure.
All of our MSc courses operate on a credit-based modular system. A standard module is typically worth 15 credits and the research project/dissertation is worth 60 credits. You are required to study 180 credits in total.
|Knowledge Representation and Machine Learning||15|
(study at least 15 credits)
|Data Mining and Text Analytics||15|
(study up to 60 credits)
|Advanced Distributed Systems||15|
|Mobile Application Development||15|
|Semantic Technologies and Applications||15|
This is an indicative list and actual content may vary as we regularly review the content of our courses in light of new experiences and developments in the field.
In an era where computational resources are cheap and all-pervasive, intelligent systems, from those embedded in widely accessible web applications, through to specialised tools for finding near-optimal solutions to hard problems, are vital for companies seeking competitive advantage.
Graduates with strong foundations in the theory and practice of intelligent systems are employed across the computing industry and in research centres.
Career pathways are therefore extremely diverse, but might include: working in a small company designing and implementing web services that adapt to clients’ history and task; deploying tools for searching medical databases to understand better the success rate and side-effects of treatments; developing products that use video stream data to make better use of a company’s resources; or using insight into biological systems to construct robotic devices
that are more robust to problems in their working environment.
A degree equivalent to a UK upper second class honours (2:1) degree or higher in computing or a related discipline with a significant computing component. You are expected to have programming competence, some prior systems development experience and knowledge of data structures and algorithms. Relevant work experience will also be taken into consideration.
We also welcome and accept students with a wide range of international equivalent qualifications.
English language requirement: A pass at GCSE level in English language (grade C or above). If English is not your first language, you are required to provide evidence of proficiency in English. You will need to meet our minimum requirements for one of the following recognised English language tests: the International English Language Testing Service (IELTS), the Test of English as a Foreign Language (TOEFL) and the Pearson Test of English Academic.
The easiest and quickest way to apply for one of our masters courses is to apply online. This way, you can also track your application at each stage of the process. However, if you prefer, you can download an application form to print out and complete. Once complete, please return this, along with the correct documents to our Engineering Admissions Hub either via email or post: Engineering PGT Admissions Hub, Faculty of Engineering, University of Leeds, LS2 9JT, UK.
If you require any further information please contact our admissions team,
e: email@example.com, t: +44 (0)113 343 5440.