Why choose this course

We’re still open for 2019 applications. If you would like to be considered for 2019 entry, please apply for 2020 entry and email Admissions with your URN to advise you would like to join us in 2019.

In our fast-paced, data-driven modern world, business analysts help organisations turn big data into big ideas.

Artificial intelligence, machine learning and management science power decisions in business. You’ll gain data-led insights and optimise businesses by using descriptive, predictive and prescriptive analytics.

Our highly practical MSc Business Analytics course will transform you into a confident lateral thinker who is up-to-date on the latest theory and practice. While you benefit from the input of inspiring industry experts, in class and on-site, we will also make sure you’re immersed in the business problems faced by the global business community today.

What you will study

This course will take your career to the next level and develop your ability to make the big decisions about data in a confident fashion. Your studies will focus on two areas: analysing business data and using data to solve business challenges. On this course, you will have an opportunity to use artificial intelligence to improve a chess game, game theory to create games, or computational intelligence with

genetic algorithms. You’ll also discover visualisations from graphs and explore virtual reality, gaining insights from data mining and machine learning. This course includes a placement module as a final project, where you’ll apply what you’ve learned in a relevant organisation.

Discover business analytics with Senior Lecturer, Dr Wolfgang Garn.

Key information

Start date: October 2020

Full-time: 1 year

Full-time (with placement): 15 months

Part-time: 2 years

Professional recognition

MSc - Association to Advance Collegiate Schools of Business (AACSB)
Accredited by the Association to Advance Collegiate Schools of Business (AACSB).

Study and work abroad

There may be opportunities to acquire valuable European experience by working or conducting research abroad during your degree or shortly afterwards. It is possible to do this in the summer period with an Erasmus+ grant working on your dissertation or as a recent graduate. In order to qualify your Erasmus+ traineeship must be a minimum of two months.

Career prospects

Business analytics students often pursue careers as:

  • Data scientists
  • Finance analysts
  • Operations researchers
  • Consultants
  • Managers
  • Analysts.

Placements

As part of this course you’ll have the opportunity to complete a Professional Training placement, where you can apply what you’ve learnt in a relevant organisation and gain practical experience for your CV.

We provide support and guidance to help you secure a placement alongside access to vacancy portals, which include thousands of placement opportunities every year and let you discover companies we’re connected with. We can also vet and support you for a placement at a new company that you approach. We don’t usually place students directly.

If you choose not to complete a placement, or do not secure a placement, you’ll complete nine months of teaching and then spend three months working on a dissertation. This means you’ll complete this course in 12 months.

If you choose and secure a placement, you’ll complete nine months of teaching and then spend six months working on placement. This means you’ll complete the course in 15 months instead of 12.

Software

You’ll get hands-on experience using a wide range of tools in the course, including:

  • Excel (using the Solver and Data Analysis add-ins)
  • Tableau or Microsoft Business Intelligence for decision making and visual analytics
  • SQL Server or MySQL for databases and structured query language
  • SAP for enterprise resource planning
  • R as the number one analytics language for machine learning, AI and prescriptive analytics
  • SPSS and EViews for decision science, statistics and forecasting
  • ILOG’s Optimisation Studio (Cplex) and MathProg (GPLK) for numerous optimisations (LP, IP, 0-1 P, MIP)
  • Simul8 and Simio for discrete event simulations and virtual reality animations.

Programme leader

FAKHIMI Masoud (SBS)

Terms and conditions

When you accept an offer of a place at the University of Surrey, you are agreeing to comply with our policies and regulations, and our terms and conditions. These terms and conditions are provided in two stages: first when we make an offer and second when students who have accepted their offers register to study at the University. View our offer terms and conditions and our generic registration terms and conditions (PDF) as a guide as to what to expect.
 
Please note: our offer terms and conditions will be available in the September of the calendar year prior to the year in which you begin your studies. Our registration terms and conditions will vary to take into account specifics of your course.

Disclaimer

This online prospectus has been prepared and published in advance of the academic year to which it applies. The University of Surrey has used its reasonable efforts to ensure that the information is accurate at the time of publishing, but changes (for example to course content or additional costs) may occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for a course with us. Read more.

Modules

Modules listed are indicative, reflecting the information available at the time of publication. Please note that modules may be subject to teaching availability, student demand and/or class size caps. 

The University operates a credit framework for all taught programmes based on a 15-credit tariff. Modules can be either 15, 30, 45 or 60 credits, and additionally for some masters dissertations, 90 credits.

The structure of our programmes follows clear educational aims that are tailored to each programme. These are all outlined in the programme specifications which include further details such as the learning outcomes:

Year 1 (full-time)

Optional modules for Year 1 (full-time) - FHEQ Level 7

Choose 1 optional module in Semester 1.
Choose 2 optional modules in Semester 2.

Students on the placement pathway must undertake the 60 credit placement module. Students NOT on the placement pathway must undertake the 60 credit dissertation module.

Year 1 (full-time with placement - 15 months)

Optional modules for Year 1 (full-time with placement - 15 months) - FHEQ Level 7

Choose 1 optional module in Semester 1.
Choose 2 optional modules in Semester 2.

Students on the placement pathway must undertake the 60 credit placement module. Students NOT on the placement pathway must undertake the 60 credit dissertation module.
The placement duration is six months.
The deadline for programme transfers between the 12 and 15 month routes is 30th May.
 

Timetable

New students will receive their personalised timetable in Welcome Week, and in subsequent semesters, two weeks prior to the start of semester. Please note that while we make every effort to ensure that timetables are as student-friendly as possible, scheduled teaching can take place on any day of the week (Monday–Friday). Wednesday afternoons are normally reserved for sports and cultural activities. View our Timetabling Policy (PDF).

Learning and disability

We have two services, Academic Skills and Development and the Disability and Neurodiversity Service which can help develop your learning.

Academic Skills and Development

Academic Skills and Development is a learning space in the Library where our learning development team is based. It comprises dedicated Student Learning Advisers and Information Skills Librarians who can help you develop your academic and research skills, including writing, presenting, revision and critical thinking.

Find out more about the study support available.

Disability and Neurodiversity Service

The University’s Disability and Neurodiversity Service supports students with disabilities, long-term health conditions, specific learning differences (such as dyslexia and dyspraxia) and other neurodiverse conditions (including autism spectrum and attention deficit disorder).

If you tell us about any conditions and register with us, we can give you appropriate support during your studies.

We can arrange exam and learning support adjustments, give advice on applications for the Disabled Students' Allowance, and test you for dyslexia and dyspraxia. We can also offer regular study skills and mentoring support.

Find out more about the support available or contact the team directly for further information.

English language support

Our English Language Support Programme (ELSP) provides tailored English language support during your studies. It is particularly valuable to students who speak English as a second or additional language, but native speakers are also welcome.

Entry requirements

A minimum of a 2:2 UK honours degree in either Computer Science, Economics, Engineering, Finance or Mathematics, or a recognised equivalent international qualification. We'll also consider a minimum of three years relevant work experience in an analytical and data-intensive field if you don’t meet these requirements.

View entry requirements by country

English language requirements

IELTS Academic: 

Full-time: 6.5 overall with 6.0 in each element.

Part-time: 6.5 overall with 6.0 in each element.

Full time with placement: 7.0 overall with 6.5 in each element.

View the other English language qualifications that we accept.

If you do not currently meet the level required for your programme, we offer intensive pre-sessional English language courses, designed to take you to the level of English ability and skill required for your studies here.

Credit transfer

The University of Surrey recognises that many students enter their higher education course with valuable knowledge and skills developed through a range of professional, vocational and community contexts. If this applies to you, a process called recognition of prior learning (RPL) may allow you to enter your course at a point appropriate to your previous learning and experience, or to join the start of a course without the formal entry requirements. This means that you may be exempt from certain elements of study in the course for which you have applied and be awarded credit based on your previous qualifications/experience. There are restrictions on RPL for some courses and fees may be payable for certain claims. 

Please see the code of practice for recognition of prior learning and prior credit: taught programmes (PDF) for further information. Please email Admissions with any queries.

Fees

Start date: October 2020

Full-time

UK/EU £12,700

Overseas £19,600

Full-time (with placement)

UK/EU £13,400

Overseas £21,100

Part-time

UK/EU £6,400

Overseas £9,800

Please note:

  • These fees apply to students commencing study in the academic year 2019-20 only. Fees for new starters are reviewed annually.
  • If you are on a two-year or three-year part-time structured masters course, the annual fee is payable in Year 1 and Year 2 of the course.

View the list of fees for all postgraduate taught courses.

How to apply

We’re still open for 2019 applications. If you would like to be considered for 2019 entry, please apply for 2020 entry and email Admissions with your URN to advise you would like to join us in 2019.

Admission information

Our postgraduate admissions policy provides the basis for admissions practice across the University and gives a framework for how we encourage, consider applications and admit students. You can also read our postgraduate applicant guidance.

Our students

Discover

Course location and contact details

Campus location

Stag Hill

Stag Hill is the University's main campus and where the majority of our courses are taught. 

Placement location

As part of this course you have the option to complete a placement which would require attendance off campus, depending on where you secure your placement.

University of Surrey
Address

University of Surrey
Guildford
Surrey GU2 7XH