Why choose this course
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.
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.
Business analytics students often pursue careers as:
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.
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.
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.
Year 1 (full-time)
Dissertation for Business Analytics
Foundations of Finance: Finance & Investments
Foundations of Statistics and Econometrics
Principles of Accounting
Supply Chaing Management and Logistics
Business Process Management (With SAP)
Informatics for Decision Making
Introduction to Marketing Analytics
Machine Learning & Visualisations
Supply Chaing Analytics
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.
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 of relevant work experience in an analytical and data-intensive field if you don’t meet these requirements.