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Web Science and Big Data Analytics MSc

The MSc covers web-related technologies and big data analytics. It is intended for students with a general science and engineering background and makes them well equipped to proceed to become the ideal choice for the best employers in internet-related industries and the areas requiring big data analytical skills.

Key Information

Modes and duration

  • Full-time: 1 year

Tuition Fees (2015/16)

UK/EU:
£10,765 (FT)
Overseas:
£22,350 (FT)

Application deadlines

All applicants:
31 July 2015

Entry Requirements

A minimum of an upper second-class UK Bachelor's degree in a highly quantitative subject, or an overseas qualification of an equivalent standard. Students should also have some experience with a programming language such as Java or python.

The English language level for this programme is: Good

Further information can be found on our English language requirements page.

International students

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.

International applicants can find out the equivalent qualification for their country by selecting from the list below.

Select your country:

Degree Information

Students will gain a detailed knowledge and understanding of web-related technologies and big data analytics, ranging from information search and retrieval, natural language processing, data mining and knowledge acquisition, large-scale distributed data analytics and cloud computing to e-commerce and their business economic models and the latest concepts of social networks.

MSc students undertake courses to the value of 180 credits.

The programme consists of five core modules (75 credits), three option modules (45 credits) and the research dissertation (60 credits).

Core Modules

  • Information Retrieval and Data Mining
  • Distributed Systems and Security
  • Multimedia Systems
  • Complex Networks and Web
  • Web Economics

Options

  • Cloud Computing
  • Computer Graphics
  • Entrepreneurship: Theory and Practice
  • Interaction Design
  • Machine Learning
  • Machine Vision
  • Statistical Natural Language Processing
  • User-Centred Evaluation Methods

Dissertation/report

All students undertake an independent research project which culminates in a substantial dissertation.

Teaching and Learning

The programme is delivered through a combination of lectures, tutorials and seminars. Lectures are often supported by laboratory work with help from demonstrators. Student performance is assessed by unseen written examinations, coursework and the dissertation.

Further information on modules and degree structure available on the department web site Web Science and Big Data Analytics MSc

Funding

Brown Family Bursary

Value:
£15,000
Duration:
1 year
Eligibility:
Prospective full-time Master's students within the Faculties of the Built Environment, Engineering Science and Mathematical & Physical Sciences.

Brown Family Bursary

Value:
£15,000
Duration:
1 year
Eligibility:
Prospective full-time Master's students within the Faculties of the Built Environment, Engineering Science and Mathematical & Physical Sciences.

Brown Family Bursary

Value:
£15,000
Duration:
1 year
Eligibility:
Prospective full-time Master's students within the Faculties of the Built Environment, Engineering Science and Mathematical & Physical Sciences.

More scholarships are listed on the scholarships website

Careers

Graduates from UCL are keenly sought by the world's leading organisations, and many progress in their careers to secure senior and influential positions. Graduates of our Web Science and Big Data Analytics programmes are expected to develop careers in scientific research, the internet-based industry and other professional areas that require big data analytics skills.

Employability

The skill set obtained from our MSc makes our students the ideal choice for the best employers in internet-related industries and sectors requiring big data analytics. The MSc has a unique industry connection as almost all our lecturers have industry experience. Through long-term collaborations with big players in the field such as Google, Microsoft and BT, research is driven by the fundamental technical challenges faced by the industry. Throughout the degree, our students have the chance to interact with our industry collaborators and previous students, and have placement opportunities to address the specific technical problems faced by the industry.

Why study this degree at UCL?

UCL Computer Science is recognised as a world leader in teaching and research, and was one of the top-rated departments in the country according to the UK government's recent research assessment exercise.

Our Master's programmes have some of the highest employment rates and starting salaries, with graduates entering a wide variety of industries, from entertainment to finance.

We take an experimental approach to our subject, enjoy the challenge and opportunity of entrepreneurial partnerships and place a high value on our extensive range of industrial collaborations.

Student / staff ratios › 80 staff › 650 taught students › 175 research students

Department: Computer Science

Application and next steps

Applications

Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

Who can apply?

The MSc programme is suitable for students with a general science and engineering background who wish to learn web-related technologies and data mining skills needed for the development of large-scale web eco systems and information seeking and quantitative data analysis tools.

Application deadlines

All applicants
2015-07-31

For more information see our Applications page.

Apply now

What are we looking for?

When we assess your application we would like to learn:
  • why you want to study Web Science and Big Data Analytics at graduate level
  • why you want to study Web Science and Big Data Analytics at UCL
  • what particularly attracts you to this programme
  • how your academic and professional background meets the demands of this programme
  • what programming experience you have
  • where you would like to go professionally with your degree
Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.

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