**Please note** This programme will not run from 2019/20. Information valid for 2018/19 only.

MSc Business Analytics provides an exciting and challenging study of how data can be utilised to solve major business and societal challenges. The programme provides students with the knowledge, technical ability and skills for leadership roles in the fields of business analytics and data science.

The programme is designed to give students multi-disciplinary skills in computing, analytics, data science and business analysis. Emphasis will be on business problem framing, leveraging data as a strategic asset, and communicating complex analytical results to stakeholders.

This programme is for the ambitious, future pioneers in industry. Only apply if you want to change the world.

The MSc Business Analytics consists of 8 taught modules and a Dissertation. Of the taught modules, 3 are core modules, with either 4 option and 1 elective modules or 3 option and 2 elective modules.

Compulsory / Core Modules

  • COMP0047 - Data Analytics (15 credits)
  • COMP0072 - Programming for Business Analytics (15 credits)
  • MSIN0093 - Business Strategy and Analytics (15 credits)
  • COMP0065 - Project in Business Analytics (60 credits)

All modules in this group are compulsory.

Optional Modules

  • COMP0088 - Introduction to Machine Learning (15 credits)
  • COMP0124 - Multi-agent Artificial Intelligence (15 credits)
  • CASA0006 - Data Science for Spatial Systems (15 credits)
  • CASA0003 - Group Mini Project: Digital Visualisation (30 credits)
  • CASA0002 - Urban Simulation (15 credits)
  • MSIN0071 - Decision and Risk Analysis (15 credits)
  • MSIN0053 - Mastering Entrepreneurship (15 credits)
  • PSYC0054 - Consulting Psychology (15 credits)
  • PSYC0057 - Consumer Behaviour (15 credits)
  • PSYC0055 - Talent Management (15 credits)
  • STAT0011 - Decision and Risk (15 credits)
  • STAT0029 - Statistical Design of Investigations (15 credits)

Choose a minimum of 45 credits and a maximum of 60 credits from the optional modules.

All choices are subject to timetabling constraints and the approval of the relevant Module Tutor and the Programme Director.

Elective Modules

  • COMP0081 - Applied Machine Learning (15 credits)
  • COMP0080 - Graphical Models (15 credits)
  • COMP0084 - Information Retrieval and Data Mining (15 credits)
  • COMP0127 - Robotic Systems Engineering (15 credits)
  • COMP0087 - Statistical Natural Language Processing (15 credits)

Choose a minimum of 15 credits and a maximum of 30 credits from the elective modules.

All choices are subject to space on modules, timetabling constraints and the approval of the relevant Module Tutor and the Programme Director.

Syllabus content for all postgraduate modules can we found in the Department of Computer Science 2018/19 online syllabus pages.

Programme diet (modules available to you)

Your programme has a set curriculum (also called a diet) which prescribes in what combinations modules can be taken, any restrictions on doing so, and how much credit can and must be taken. The programme information pages show which modules form part of each programme, with links to descriptions and module syllabus information. Modules within a programme can be core, optional, or elective, which reflects whether they must be taken or are optionally taken.

Core modules

Core modules are fundamental to your programme’s core curriculum and are mandatory. You will automatically be registered on your programme's core modules, so will not have to select them. You are guaranteed a place on modules that are core for your programme. There will be no timetable clashes between core modules within a programme.

Optional modules

Optional modules are usually closely related to the programme's core curriculum and you will be able to choose which to take; choices are usually made from within specific groups (for example, choose two optional modules from one group and three from another, etc.) You are not guaranteed a place on optional modules as space is strictly limited. We allocate places on a first come, first serve basis, with preference given to Computer Science students over those of other departments. Bear in mind that some modules have prerequisites that must be met in order to be eligible for a place (see the module syllabus for information.)

Elective modules

Elective modules are usually not specifically related to the programme's curriculum. There is no guarantee of being accepted onto an elective module; they are core and/ or optional on other programme diets, so students on those programmes will be given priority. As with optional modules, some electives have prerequisites that must be met.

Deciding which modules to select

The programme information pages show which modules form part of each programme, with links to detailed module syllabus information and reading lists. You may be able to virtually audit lectures for some modules to get a sense of how the module is delivered. You can look up the timetable for each module via the common timetable to get a sense of the timetable that would eventuate from your module choices, which is an important consideration when making your final choices; you should aim to achieve a timetable that is feasible and will not stretch you too thinly.

Bear in mind that places on optional and elective modules are not guaranteed, so you might not always be able to take all your first choices. In that case, it is a good idea to have a second preference in mind.

If you need guidance with choosing which modules to select then please contact your Programme Director or the Departmental Tutor.

A minimum of an upper second-class UK Bachelor's degree (or overseas equivalent) in a quantitative subject as computer science, engineering, mathematics or physics.

English Language Requirements

If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.

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.

Funding Opportunities

The Department of Computer Science is offering Excellence Scholarships to our taught postgraduate students. To check your eligibility and to apply, see the Computer Science Excellence Scholarship application form.

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarship and Funding website.

Tuition Fee Deposit

This programme requires that applicants firmly accepting their offer pay a deposit. This allows UCL to effectively plan student numbers, as students are more demonstrably committed towards commencing their studies with us.

For full details about the UCL tuition fee deposit, please see the central UCL pages.

Tuition fee deposits within the Department of Computer Science are currently listed as:

*only applicable where part-time is an available mode of study

This programme is designed to satisfy the need, both nationally and internationally, for exceptional data scientists and analysts. Graduates from this new programme will be highly employable and they will be equipped to influence strategy and decision-making, and be able to drive business performance by transforming data into a powerful and predictive strategic asset. We expect our graduates to progress to leading and influential positions in industry.

Graduate Destinations

Graduates from the Department of Computer Science are particularly valued as a result of the department’s international status, and strong reputation for leading research. Recent graduate destinations include:

  • IBM
  • Samsung
  • Microsoft
  • PwC
  • Citibank

Careeer Support

Our dedicated team works directly with students to provide tailored individual career support, facilitate connections with employers globally, and enhance employability. Additional support is provided by the Careers Service who run training sessions, workshops, networking events and careers fairs.


UCL Advances aims to promote interaction among researchers, businesses, industry, investors and students. They support our entrepreneurially minded students by providing training, business support services and funding.

Programme Administrator

Samantha Bottomley

Office: 5.22, Malet Place Engineering Building

Telephone: +44 (0) 20 7679 0328

Email: advancedmsc-admissions@cs.ucl.ac.uk

Click here for more information

Programme Director: Dr Daniel Hulme