Start date: September 2023
Duration: 12 months full-time
Fees: UK - £21,200, and Overseas - £38,300
Application deadline: Applications open on 17 October 2022 and close on 31 March 2023 (please note that this is subject to change if the programme is filled before this date)
Entry: Minimum of 2:1 honours or equivalent in a relevant discipline. International students, please note that UCL’s English language requirement for this programme is a 'Level 2' - further details regarding this can be found at the UCL English Language Requirements page.
The global economy is changing. Businesses are becoming more complex and interconnected. Organisations are generating and capturing trillions of bytes of information about their customers, suppliers and operations. And the technology, tools and platforms for analysing this data are evolving incredibly fast. This explosion of complexity, data, and technology is disrupting industries and creating new opportunities.
But understanding the technology alone isn’t enough.
The world’s leading companies need people who understand how management best practices are evolving to adjust to this new deeply complex, interconnected and data-driven world.
People who can take data and transform it into a powerful strategic asset – people who deeply understand data, its potential and its limitations, who can frame complex data-driven business problems, analyse data with the right statistical techniques, employ the latest analytics tools and methods, and communicate analytics results to business executives, partners and customers.
The UCL Business Analytics programme provides a rigorous, practical foundation in these critical skills and provides a platform for careers with global companies and high-growth businesses tackling world-scale problems.
UCL’s Business Analytics Master’s degree programme provides a rigorous, practical foundation in the key skills needed to unlock the value of data, and an in-depth understanding of how companies can use data to make decisions and improve business performance. It combines modules that explore how data and analytics are transforming key areas of business (decision-making, strategy, marketing, operations) with modules that provide students with the mathematical and computational foundations needed to make effective and intuitive use of the latest business analytics tools and platforms.
Graduates from this London-based master’s programme will be highly employable in global companies and high growth tech businesses, finance and banking organisations and consulting firms. They will be equipped to influence strategy and enhance decision-making and be able to drive business performance by transforming data into a powerful strategic asset.
During the year, students undertake six core modules, two optional modules and complete a Consulting Project/Dissertation.
During the year, students undertake six core modules, two optional modules and complete a Consulting Project/Dissertation.
The programme is delivered through a combination of lectures, seminars, tutorials and project work. Assessment is through examinations, individual coursework, group coursework and a dissertation project.
Students typically study 4 modules in Term 1 and 4 modules in Term 2, of which two are selected from the optional module list. In Term 3 students undertake a supervised dissertation project.
Each taught module is delivered over 10 weeks, with 3 contact hours per week comprising lecture content and interactive components. Some of the modules may have additional workshop sessions.
In addition, students spend approximately 7-12 hours a week for each module on assessment and independent study to further develop the skills and knowledge covered in lectures and seminars. The total number of weekly hours will vary according to the weekly activities being undertaken.
To view information about the modules on this programme, enter the module code (eg MSIN0093) in UCL’s Online Module Catalogue.
Core modules in Programming for Business Analytics and Predictive Analytics in Terms 1 and 2 respectively, provide a foundation in delivering an analytical solution that flows naturally into the Term 3 Consulting Project/Dissertation.
These modules are complemented by Statistical Foundations for Business Analytics which ensure that students have the necessary statistical skills to make effective use of the latest analytics methods and tools. Business Strategy and Analytics focuses on how companies create value and competitive advantage in complex, innovation-intensive, data-driven environments.
Additional core modules in Marketing Analytics and Operations Analytics explore in greater depth how data and analytics can unlock value in these key areas and build the insight and skills required to define and deliver practical, high-impact business analytics projects that improve business performance.
This provides a foundation in how companies create value and competitive advantage in complex, innovation-intensive, data-driven environments. It will introduce strategy frameworks for goal setting and performance evaluation, and examine the descriptive, explanatory and predictive nature of data. Ethics, privacy and security considerations will be discussed.
Marketing Analytics addresses how to use data analytics to learn about and market to individual customers. This course examines the premise behind customer-centric marketing, helps you understand the customer lifecycle and customer profitability, and introduces analytical and statistical modeling of customer information.
Underpinning the new analytics that are transforming key areas of business is foundational mathematics. This course will refresh your knowledge of algebra, statistics and calculus before moving onto econometrics with various Bayesian and regression models. It concludes with an introduction to the mathematical basis for supervised and unsupervised approached to machine learning.
Computational models and concepts for business analytics need to be implemented with tools and technologies. The course will cover computational thinking, experimental methodology, preparing datasets and empirical methods for training, validation and testing models. Practical sessions will provide a general introduction to programming in Python and look at standard implementation of useful algorithms.
Predictive Analytics will build on the foundational courses in Term 1 to explore techniques from data mining, statistics, modelling and machine learning in greater detail. We will analyse current data to make predictions about future events across a variety industry use cases with support specific companies and practitioners.
This course explores in greater depth how data and analytics can unlock value in these key business areas and build the insight and skills required to define and deliver practical, high-impact business analytics projects that improve business performance.
Students undertake a practical consulting project or an independent research-based project, which culminates in a dissertation of 12,000 words.
Students take two optional modules. They are likely to be from the following list of elective modules offered by the UCL School of Management. The optional modules are designed to develop practical analytical skills that are in high demand by potential employers.
The finalised list of optional modules offered for the 2022/23 academic year is as stated below.
The optional modules listed are subject to change each year and are indicative only. Optional modules can change for a variety of reasons including but not limited to updated learning outcomes, lack of demand and resourcing. For questions about optional modules, please reach contact us via email at: firstname.lastname@example.org.
The teaching team brings together people with experience of how companies are evolving their management practices in a complex, interconnected and data-driven world and how they are employing the latest business analytics platforms and tools to make decisions and improve business performance. Module Leads can be found on their relevant module catalogue pages.
The core teaching team includes:
David Alderton, Programme Director
Alastair Moore, Assistant Professor
Anil Doshi, Assistant Professor
Zhenyu Zhang, Assistant Professor
Lina Song, Assistant Professor
Wei Miao, Assistant Professor
Full-time (one year):
mid-September 2023 - mid-September 2024
The majority of classes are taught at Level 38 and Level 50, One Canada Square, Canary Wharf, which is UCL’s home within London’s global business district. Some optional modules will take place at the Bloomsbury campus, which will also be open to students.
Our students are, and always have been, selected on the basis of their talent and potential, whatever their personal, social or national background.
UCL was the first English university to admit students regardless of race, class or religion, and the first to admit women students on equal terms with men.
UCL degree programmes require our students to think critically and creatively, to tackle ambitious projects and to develop the leadership and entrepreneurial skills that will stand them in excellent stead for their future lives and careers. Our innovative evolving Business Analytics MSc programme embodies this approach to postgraduate study.
We are looking for intellectually curious, self-motivated students who are passionate about business, technology and data. You will join an international cohort of students drawn from a wide variety of backgrounds.
The minimum entrance requirements are an upper second-class Bachelor’s degree from a UK university or an overseas equivalent and a strong aptitude for quantitative analysis. Applicants are likely to have studied a range of degrees including business, engineering, computer science, economics, and psychology.
We are aiming to prepare the next generation of “data native” leaders who are able to take data and transform it into a powerful strategic asset.
We would like to understand how the programme could help you achieve your career goals, and what skills will you will bring to the class.
When we assess your application we will be seeking to learn:
- Why you want to study Business Analytics at a postgraduate level;
- What particularly attracts you to this programme and to UCL;
- How your academic and professional background meets the demands of this challenging programme;
- What your post-degree aspirations are.
The personal statement is an opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.
The 2023-24 fees are available online.
Course fees are administered by the Student Fees Office. For more information on fees and financial support, please visit: UCL Prospective Student – Fees and Funding page.
Scholarships are available through UCL for all years of study. Competition for scholarships is fierce, however, and to stand a chance of being chosen you will need to show evidence of commitment and the potential for high achievement.
Application for scholarships and bursaries must be made either when confirming your place before the start of your studies.
We are looking for intellectually curious, self-motivated students who are passionate about business, technology and data.
- Academic Profile: The minimum entrance requirements are an upper second-class (2:1) Bachelor’s degree from a UK university or an overseas equivalent and a strong aptitude for quantitative analysis. Applicants are likely to have studied a range of degrees including business, engineering, computer science, economics, and psychology. International Students may ascertain qualification equivalents from the UCL international students website. UCL Admissions check qualification equivalencies before forwarding application forms to our School. The UCL School of Management is unable to comment on international qualifications.
- Career Aspirations: Focused on helping global companies and high-growth businesses use business analytics to tackle world-scale problems.
- English Language Skills: Applicants whose first language is not English must be able to provide evidence that their spoken and written command of the English language is adequate. UCL’s preferred English language qualification is the International English Language Testing System (IELTS). A ‘Level 2’ is required for the Business Analytics: i.e. an overall grade of 7.0, with a minimum of 6.5 in each of the subtests.
- Application Process: Qualifications are assessed only once an application has been submitted. The equivalency of overseas qualifications cannot be assessed unless a full application with all supporting documentation such as degree transcripts, references, etc. has already been submitted to UCL.
Applicants who meet the entry requirements and are suitable for the programme may be invited for an online interview via Kira Talent. Applicants invited to interview will have a window of 7 calendar days from receipt of the email to complete the interview. An applicant’s failure to complete their interview within this window would lead to an unsuccessful application.
For further information regarding the Business Analytics MSc please contact the Programme Administrator via: email@example.com. For further queries regarding admissions please see the UCL Postgraduate Admissions Webpage.
All full time students are required to pay a fee deposit of £2,000 for this programme. This programme does not have any compulsory additional costs outside of purchasing books or stationery, printing or photocopying.
This programme may include opportunities for students to undertake optional international study trips. The costs of such trips are usually covered by students although some elements may be subsidised or grants available depending on the destination, organisational and support responsibilities. On average, costs would be around £1,000 to £1,750 depending on the trip location, personal flight preferences and spending habits as well as the prevailing exchange rates.
For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs.
Why choose us
UCL is one of the world’s very-best universities, consistently placed in the global top 20 in a wide variety of world rankings.
UCL’s Business Analytics is unlike any other degree in the UK. It provides you with an opportunity to develop an in-depth understanding of how companies are transforming data into a powerful strategic asset and a rigorous foundation in the key skills needed to build a successful career in global businesses.
The programme is taught by the UCL School of Management, which is focused on creating disruptive research and entrepreneurial leaders for the complex, interconnected world of the future.
The Business Analytics MSc
- Provides students with in-depth knowledge and understanding of business analytics
- Prepares students for working in a complex, interconnected, data-driven environments
- Delivers practical experience of applying new learned skills to a real business problem
- Prepares students for jobs in industries and organisations characterised by rapid changes in problems, opportunities and tools
- Enables students to develop the awareness, background, and skills necessary to become responsible citizens, employees, and leaders who can make a contribution to tackling some of the world’s most difficult social and economic problems
In particular, the programme will help students develop:
- A critical appreciation of data, its potential and limitations, and how data can be used to improve business decision-making, and create value and competitive advantage in complex, interconnected, data-driven environments
- A knowledge and understanding of relevant statistical and computational techniques and how they can be applied in practice to business analytics problems
- An understanding of how data and analytics can provide the basis for new business models and new products and services
- The insight and skills required to frame business analytics problems, and define and deliver practical, high-impact business analytics projects that improve business performance
- An understanding of the opportunities to unlock value through business analytics in specific management areas, e.g. strategy, marketing, operations
- An ability to communicate analytics results effectively to non-specialist audiences, including business executives, partners and customers.
- A knowledge of contemporary issues necessary to understand the impact of business analytics in a global and societal context.
Join us on Tuesday 31 January 2023 for our virtual information session with Programme Director David Alderton. During the session, you will have the opportunity to get an insight into the programme and out your questions to the Programme Director and current students to give you an overview of the programme and what it’s like to study with us.
Our careers team work with students to enhance their employability, provide tailored individual careers support and facilitate connections with employers globally. Please visit our Careers page for further information.
UCL is consistently ranked as one of the world’s very best universities and employers are keen to meet our students to discuss the opportunities they offer. In addition to the bespoke activities within the School of Management, you also have access to the central UCL Careers provision.
Graduates from this programme will be highly employable in global companies and high growth businesses, finance and banking organisations and consulting firms. They will be equipped to influence strategy and decision-making, and be able to drive business performance by transforming data into a powerful strategic asset.
The 2018-2019 Graduate Outcomes Survey shows that 96.9% of those surveyed (and who are eligible to work or study) secured highly-skilled work, or HE-level study within 15 months of graduating from the MSc Business Analytics programme. The graduates have found jobs in a variety of high-profile companies including:
- Bloomberg LP
- Burberry Ltd
- Charles Taylor
- Chongqing Changan Ltd
- Dice FM
- Dongseng Nissan Aupo Assignment
- FDM Group Ltd
- HSBC Bank plc
- KPMG LLP
- Montessori School
- Sia Partners
- The Oxford-Partnership
- UBS Investment Bank
- Visa Europe
- XAI Asset Management
- ...and many more