MSc Business Analytics

An upper second-class undergraduate honours degree or international equivalent in any of the following subjects:

Operational Research, Management Science, Decision science, Mathematics, Statistics, Data Science, Finance (not Accounting and Finance), Economics, Computer Science, Physics, Engineering, Biomedical/Life Sciences.
OR

An upper second-class honours degree or international equivalent in any discipline that includes 65% or above in at least 2 quantitative units. Examples of acceptable units include:

Advanced Maths / Algebra /Analysis /Bayesian Modelling /Calculus /Complex Functions /Decision Maths /Differential Equations / Ordinary Differential Equations /Discrete Mathematics /Econometrics /Financial Maths /Game Theory /Geometry  /Information Theory /Kinematics /Kinetics /Quantum mechanics /Quantum computing /Linear Algebra /Linear Programming /Macroeconomics / Economics III / IV) /System dynamics /Thermodynamics /Complex systems/equilibrium /Mathematical Programming /Maths/mathematical methods/mathematical models/mathematical skills /Maths for Business / Business Maths /Maths for Economics /Mechanics (any type of mechanics) /Microeconomics (inc intermediate / advanced)/ Economics III / IV) /Multi Variate Analysis /Network Science /Number Theory  /Optimisation /Probability (including stochastic models/methods (e.g. Markov chain model, monte carlo models)) /Proof / Intro to Proof /Pure Maths /Quantitative Methods /Statistics/Statistical Methods/Statistical Analysis etc /Time Series Analysis /Forecasting / Physics/Physical computing /Electronic/electrical engineering /Electricity and magnetism /Engineering materials /Geotechnical /materials/structural engineering /Analytical chemistry /Simulation /Probability /Computer Science (incl programming/algorithms) /Mechatronics /Data Mining/Data Science/ Data Analytics/business analytics /Management Science /Decision Analysis and Simulation; decision science /Operational research /Derivatives /Econometrics /Financial Modelling /Quantitative techniques (intro/ advanced) /Quantitative Methods /Quantitative Research Methods /Statistics/Statistical Methods/Statistical Analysis etc /Social network analysis /Computational research methods in the social sciences /Any computational methods /Machine learning /Robotics /Experiment (e.g. experimental design, studies or research; control trials) /Research methods in health/medical/biomedical/natural sciences.

For applicants who are currently completing a degree, we understand that their final grade may be higher than the interim grades or module/unit grades they achieve during their studies.

We will consider applicants whose interim grades are currently slightly lower than the programme’s entry requirements. We may make these applicants an aspirational offer. This offer would be at the standard level, so the applicant would need to achieve the standard entry requirements by the end of their degree. Specific module requirements may still apply.

We will consider applicants whose grades are slightly lower than the programme’s entry requirements, if they have at least one of the following:

• evidence of significant (minimum of 6 months in a paid role) relevant work experience in sectors such as Digital Marketing, Data Science, Data Engineering, Banking and Finance or roles which require expertise in data analytics or statistics.
• a relevant postgraduate qualification.

If this is the case, applicants should include their CV (curriculum vitae / résumé) when they apply, showing details of their relevant work experience and/or qualifications.

For fees and funding options please visit website to find out more