Scientific Computing and Data Analysis (Computer Vision and Robotics) at Durham University - UCAS

Durham University

Degree level: Postgraduate

Scientific Computing and Data Analysis (Computer Vision and Robotics) (Taught)

Course options

Course summary

Advances in fields such as Robotics, Physics, Engineering, Earth Sciences or Finance are increasingly driven by experts in computational techniques. Notably, people skilled to write code for the most powerful computers in the world and skilled to process the biggest data sets in the world can truly make a difference. The MSc in Scientific Computing and Data Analysis offers an application-focused course to deliver these skills with three interwoven strands:

  • Computer Science underpinnings of scientific computing (algorithms, data structures, implementation techniques, and computer tool usage)
  • Mathematical aspects of data analysis
  • Implementation and application of fundamental techniques in a domain specialisation (presently astrophysics, particle physics, financial mathematics, robotics or earth and environmental sciences).
MISCADA’s Computer Vision and Robotics specialisation aims to equip students with the background needed to address some of the biggest research questions in robotics and its associated sensing algorithms, such as how we can develop future autonomous mobility solutions in a safe and reliable manner. The courses include computer vision, machine learning, robotic motion and planning in addition to reinforcement learning.

Modules

The course is structured into five elements spanning three terms. In this course: you will obtain a strong baseline in methodological skills; you will study selected topics from your chosen specialisation area with a strong emphasis on computational and data challenges; you can choose to put emphasis on data analysis or scientific computing; you will do a challenging project either within the methodological academic departments (Mathematical Sciences or Computer Science), or within the specialisation area, or in close cooperation with our industrial partners; you will acquire important professional skills spanning collaboration and project management, presentation and outreach as well as entrepreneurial thinking.

Assessment method

The course is taught using a wide range of learning research-led and teaching methods: Lectures; Practical classes/computer labs; Independent study, research and analysis; Project (dissertation) and coursework; Group and individual presentations.


Entry requirements

A UK first or upper second class honours degree (BSc) or equivalent: In Physics or a subject with basic physics courses OR; In Computer Science OR; In Mathematics OR; In Earth Sciences OR; In Engineering OR; In any natural sciences with a strong quantitative element.


English language requirements

Durham University welcomes applications from all students irrespective of background. We encourage the recruitment of academically well-qualified and highly motivated students, who are non-native speakers of English, whose full potential can be realised with a limited amount of English Language training either prior to entry or through pre-sessional and/or in-sessional courses. It is the normal expectation that candidates for admission should be able to demonstrate satisfactory English proficiency before the start of a programme of study, whether via the submission of an appropriate English language qualification or by attendance on an appropriate pre-sessional course. Acceptable evidence and levels required can be viewed by following the link provided.

English language requirements

https://www.durham.ac.uk/study/international/entry-requirements/english-language-requirements/


Fees and funding

Tuition fees

England £13500 Year 1
Northern Ireland £13500 Year 1
Scotland £13500 Year 1
Wales £13500 Year 1
Channel Islands £13500 Year 1
EU £30900 Year 1
International £30900 Year 1
Republic of Ireland £30900 Year 1

Additional fee information

The tuition fees shown are for one complete academic year of full time study, are set according to the academic year of entry, and remain the same throughout the duration of the programme for that cohort (unless otherwise stated).
Scientific Computing and Data Analysis (Computer Vision and Robotics) at Durham University - UCAS