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The award

How long you will study
12 months

Domestic course fees
GBP 23000 per year

How you will study

Course starts

International course fees
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All study options

About Business Analytics at City, University of London


Who is it for?

Our proposed programme is designed to provide a foundation for those who will determine the scope and direction of data analytics research within an organisation, and communicate the research outcomes to the ultimate decision-makers. Our graduates are trained to participate in the strategic management process, improve the financial performance and advise about designing effective measures of performance of an organisation for which evidence-based data becomes a strategic asset in the decision-making process. Therefore, the primary goal is to provide an insight into business data analytics and prepare the students to develop the set of skills and attitudes that will evolve into effective leadership skills.


This programme is subject to approval later in the year. Course content may change.

The main purpose of the programme is to develop a comprehensive set of skills and encourage positive attributes that are essential to becoming a successful business analyst.

The degree is committed not only to creating specialist skills, but also to developing the so-called ``soft skills' aimed to influence people and organisations. Besides achieving effective and persuasive communication, the module leaders draw attention over ethics-related issues, which is another key ingredient to responsible leadership.


  • Extract valuable information from the data in order to create competition advance
  • Make use of analytical skills to evaluate and solve complex problems within the organisation's strategic perspective
  • Present and explain data via effective and persuasive communication
  • Show commercial focus and the ability of strategic thinking
  • Demonstrate depth and breadth of using analytical skills to interrogate data sets
  • Illustrate professional integrity and show sensitivity towards ethical considerations.

Pre-study modules

The MSc in Business Analytics starts in the summer before the beginning of Term 1 with three compulsory pre-courses which ensure that every student has the minimum specific background required by all other modules.

  • Introduction to Python

    This module is designed to provide a fundamental understanding of Python programming and no previous programming experience is expected. The teaching model is learning by doing and basic concepts are discussed in an incremental manner. The online material is formulated via multiple Python code examples that enable the students to work independently when dealing with small Python programming tasks.

  • Introduction to R Programming

    This module is designed to provide a fundamental understanding of R programming and no previous programming experience is expected. The teaching model is learning by doing and basic concepts are discussed in an incremental manner. The online material is formulated via multiple R code examples that enable the students to work independently when dealing with small R programming tasks.

    This module is designed to prepare you for understanding and performing the computer based exercises and tasks that you encounter in all core MSc in Business Analytics modules and will therefore be completed prior to beginning your course.

  • Professional Ethics and Good Academic Practice

    This module aims to cultivate your awareness of some key ethical issues prevalent in data analysis and statistics, in particular those issues emerging in the applications of modern data science.

    You will also develop your awareness of what constitutes good academic practice and learn how to properly reference your work and avoid issues such as plagiarism and poor scholarship in your work.

Term 1

Core modules:

  • Leadership and Organisational Behaviour

    Lectures, guided discussion, case studies, videos and group exercises should be expected. In addition, the students are encourage to make considerable use of their personal experience, both for testing theoretical ideas and for use as living case studies.

    When a business leader is invited, he/she will talk frankly and openly to the class about their methods and experience within a particular sector. This part of the class is presented as a Q&A, led by the lecturer, but enabling you to ask your own questions. Further, once the interviewee has left, you will discuss their responses and approach within a case study context.

  • Network Analytics

    This module provides on overview of various frameworks and algorithms used in practice to describe and analyse network data―namely information about relations among decision makers (e.g., customers), objects (e.g., products), or decision makers and objects (e.g., customer-product ties). You should expect to grasp the logic behind modern network science from a practical standpoint. Standard computing skills in Python are required to put in practice the theory discussed during the lectures.

  • Data Visualisation

    This module provides design principles along with frameworks and techniques to synthesise and illustrate complex information via data visualisation, which enables to understand the significance of data by placing in a visual context. You should expect to learn different approaches to data visualisation (e.g., pattern recognition or 'data storytelling') and to mobilise these approaches in order to reach various types of audiences.

  • Quantitative Methods

    Fundamental quantitative concepts and methods are introduced in this module by familiarising you with the necessary theoretical background followed by extensive computer-based real life business applications that are meant to develop basic practical skills for approaching any basic data analytics task. This module teaches you essential probability and statistical concepts useful to understand more complex analytical tools developed in all other modules and provides the foundation of using the R programming language to translate the theory into practice.

Term 2

Core modules:

  • Analytics Methods for Business

    This module provides a collection of standard analytical methods and explains how data analysis is performed in the real world. Practical solutions are developed and represent an introduction to specific tasks that a business analyst has on a daily basis that ultimately would help in analysing, communicating and validating recommendations to change the business and policies of an organisation.

  • Machine Learning

    This module provides on overview of various machine learning concepts, techniques and algorithms used in practice to describe and analyse complex data, and design predictive analytics methods. You should expect to grasp the main idea and intuition behind modern machine learning tools from a practical experience. Standard computing skills in R and Python are required to put in practice the theory discussed during the lectures.

  • Revenue Management and Pricing

    The Revenue Management and Pricing module explains how firms should manage their pricing and product availability policies across different selling channels in order to optimise their performance and profitability. The module aims to explain quantitative models needed to tackle a number of important business problems including capacity allocation, markdown management, e-commerce dynamic pricing, customised pricing, demand forecasts under market uncertainty etc.

  • Strategic Business Analytics

    This module teaches you how to design, validate and communicate business strategies by using quantitative techniques encountered in all other core MSc in Business Analytics modules. A strategic consulting approach through real-life case studies is the key ingredient of the module that enables the module leader and invited speakers, to illustrate the scope of modern business analytics by providing expert solutions to various chosen real-world problems. The analytic methods do not play the leading role and instead, you are trained to develop complex analytical problem-solving skills and hone the critical thinking of a future business analyst.

Term 3

In term three you will study:

  • An Applied Research Project (20 credits)
  • Four electives (10 credits each).

Research Project

  • Applied Research Project

    The aim of this module is to enable you to demonstrate how to integrate your learning in core and elective modules and then apply this to the formulation and completion of an applied research project. You will be required to demonstrate the skills and knowledge that you have acquired throughout your MSc study.

    You will undertake a short piece of applied research on a question of academic and/or practical relevance. Guidelines will be provided in order to help you identify the research question. Based on your chosen topic, you must write a report of around 3,000–5,000 words that summarises and critically evaluates your method and your findings.

Assessment methodsAssessment methods

Assessment methods


To satisfy the requirements of the degree course, students must complete:

  • Eight core modules (15 credits each)
  • Four elective modules (10 credits each)
  • Applied Research Project (20 credits).

Assessment of modules on the MSc in Business Analytics, in most cases, is by means of coursework and unseen examination. Coursework takes a variety of formats and may consist of individual or group presentations/reports, set exercises or unseen tests.

Induction weeks

There is a compulsory two week induction just before Term 1 starts, which is a dedicated introduction to the course and to business analytics. You are required to complete a number of induction workshops at the beginning of the course as follows:

  • Team building
  • Career induction and careers fair
  • Professional development skills.


How to apply

Documents required for decision-making

  • Transcript/interim transcript
  • CV
  • Personal statement (500-600 words)

Documents also required (may follow at later date)

  • IELTS/GMAT reports
  • Two references, one of which MUST be an academic reference
  • Work experience is not a requirement of this course, applicants with in excess of three years of experience should consider the MBA programme
  • For a successful application to receive an unconditional status all documents must be verified, so an original or certified copy of the degree transcript must be sent by post to Specialist Masters Programme Office, 106 Bunhill Row, London, EC1Y 8TZ, UK

We cannot comment on individual eligibility before you apply and we can only process your application once it is fully complete, with all requested information received.

Individual Appointments

If you would like to visit us to discuss your application please do arrange an individual appointment.

Entry requirementsGMATEnglish language requirementsEntry requirements

Entry requirements

A UK upper second class degree or above, or the equivalent from an overseas institution.

Some level of previous study in finance or quantitative methods is preferred.



GMAT is recommended for students wishing to apply for this course.

English language requirements

English language requirements

If you have been studying in the UK for the last three years it is unlikely that you will have to take the test

If you have studied a 2+2 degree with just two years in the UK you will be required to provide IELTS results and possibly to resit the tests to meet our requirements.

Study options for this course

Notes about fees for this course


£23,000 Tuition fees are subject to annual change

Fees in each subsequent year of study (where applicable) will be subject to an annual increase limited by the All Items Retail Prices Index. We will confirm any change to the annual tuition fee to you in writing prior to you commencing each subsequent year of study (where applicable).

Deposit: £2,000 (paid within 1 month of receiving offer and non-refundable unless conditions of offer are not met)

First installment: Half fees less deposit (payable during on-line registration which should be completed at least 5 days before the in-person ID–checks)
Second installment: Half fees (paid in January following start of course)

Information about Scholarships

Entry requirements

Contact City, University of London to find course entry requirements.

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