Business Analytics BSc (Hons)

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Key information

UCAS code: N9N3

Duration: 3 years

Attendance mode: Full-time

Fees: From £9,790 (more information)

Location: Clerkenwell campus

Start of programme: September 2026

Application deadline: January 2026

Entry year: Showing course information for 2026

View 2027 course information

Develop the skills to make and evaluate data-led business decisions in the modern business world

Overview

Business Analytics BSc (Hons) Who is it for?

You will be trained how to use data as one of the most useful resources of any organisation, to maximise the business's potential through data-driven solutions. This is in response to the job market's massive demand of graduates with contemporary skills that create business value by deploying complex analytical, computational, and quantitative skills.

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Our Business Analytics degrees will help you develop the skills to make and evaluate data-driven business decisions. Through a modern teaching approach and experiential learning, you will better understand the multidisciplinary nature of business and how to apply newfound skills in different business contexts. 2 minutes

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Why choose this course?

3rd in the UK for Business Administration and Finance research (ShanghaiRankings’s Global Ranking of Academic Subjects 2022)

Multidisciplinary course design includes industry sponsored projects and modern teaching approaches that account for work experience

Course objectives

The Business Analytics course has a modular approach as follows:

Core Development – Year 1 and Term One of Year 2
Core Specialisation – Term Two of Year 2
Deployment Specialisation – Year 3

On successful completion of the Core Development Stage, students will have acquired a foundational knowledge and understanding of the key concepts and principles underlying your area of study, the ability to recognise and explain them, and to identify and apply appropriate solutions when presented with a problem.

On successful completion of the Core Specialisation Stage, students have built on the knowledge and understanding gained at the Core Development Stage and demonstrated an ability to analyse and apply these concepts and principles to complex problems and scenarios.

In the Deployment Specialisation Stage, students are able to develop a very distinctive range of knowledge and skills which will supplement the objectives that underline the course as a whole. Students may also produce a final year project which provides you with work experience by delivering an industry sponsored project.

Teaching staff

Course director:

Dr Jack Fosten

Reader in Data Analytics

Course content

A rigorous teaching approach is chosen to deliver the underlying academic knowledge, which is combined with practical industry-related elements that are essential for enhancing your employment outcomes.

A testament to the modern teaching approach that will be provided in these two courses is its bespoke course structure. This includes the following elements of experiential learning:

Bootcamps (developing cutting-edge technology skills),
knowledge integration modules (developing analytical thinking skills),
work experience knowledge integration module (developing actionable insights skills),
modules that deliver work experience (micro-placements and summer internships), and
industry sponsored projects.

In line with City St George's, University of London’s Career Application Programme the industry sponsored project serves as a work experience knowledge integration module and follows the successful model delivered by the Business Analytics Industry Partnership Programme to MSc in Business Analytics since 2018 where all our postgraduate Business Analytics students have been provided with industry sponsored projects.

Besides many accounting, financial litigation, insurance and marketing consulting companies, and well-known UK retailers and wholesalers, other business partners are Bank of England, Fiat Chrysler Automobiles UK, Maserati, Rolls-Royce, the UK Government Actuary's Department, the UK National Health Service, Vodafone UK, etc.

Course structure

Core modules

Finance and Investment
This module introduces the role of finance in investment decisions and the major financial instruments used by businesses and investors.

It introduces discounting as a tool for making financial decisions, and then considers the major financial markets (bonds, equities, FX and derivatives).
Introduction to Management
This provides an introduction to management and organisational behaviour concepts.

You will study how management concepts have evolved over the years and discuss how they are relevant to your own future work as managers.
Mathematics for Business Analytics
This module provides an introduction to the fundamental mathematical concepts and techniques used in data and business analytics to aid practical data-driven decisions, with illustrations to relevant problems.

It gives you the mathematical foundations that are necessary in the subsequent specialist Business Analytics and Data Science modules.
Data Visualisation
This module provides design principles along with frameworks and techniques to synthesise and illustrate complex information via data visualisation, which enables you to understand the significance of data by placing it in a visual context.

This module is a journey into the art and science of creating memorable charts that grab the attention of a wide range of audiences and successfully convey insights and narratives.
Business Economics
This provides a grounding in Economics.

You will learn about a range of concepts used by economists and will study how these are important to managers in business.
Statistics for Business Analytics
This module introduces the essential statistical concepts used in data science and data analytics, with illustrations focused on business and finance applications.

Fundamental knowledge is rigorously covered in this module that will help you understand all future analytics methodologies.

This module also provides R training, and an R Bootcamp is scheduled.
Unsupervised Machine Learning
This module provides a comprehensive overview of unsupervised machine learning techniques, which seeks to uncover the inherent structures and groupings within the data.

You should expect to learn a variety of unsupervised learning techniques and have hands-on experience to apply those techniques to tasks in the business world, such as customer segmentation to understand the behaviours of customers for better marketing strategies.
Data Wrangling and Exploratory Data Analysis
This module introduces you to data wrangling, which is the process of cleaning, transforming, and organising raw data into a structured and usable format for data analysis.

In addition, exploratory data analysis training is provided, which is an approach in data analysis that involves visual and statistical summarising, inspecting, and understanding of the main characteristics of a dataset.

This module also provides Python training, and a Python Bootcamp is scheduled.

Career Activation Programme

As a City St George's undergraduate student you have the award winning* Career Activation Programme in your course. This means that you have a core module in which you'll learn about your career options for your subject and how to stand out to employers and you'll gain professional experience during
your course, either by completing a work-based learning module or a year placement. More details about the Career Activation Programme, and view the Career Activation Programme modules for your course.

*ISE Best University and Employer Engagement Strategy 2024

Core modules

Applied Business Intelligence
This module focuses on modern tools to easily interact with and analyse small and massive datasets.

In particular, you should expect to learn effective methods to extract relevant information from real-world business data, present findings, make informed business decisions, and set realistic goals.

This module also provides Tableau training, and a Tableau Bootcamp is scheduled.
Applied Natural Language Processing
This module focuses on modern frameworks and tools to analyse massive datasets containing `natural language’ data―e.g., economic-financial reports, press releases, speeches, or online product reviews.

The students should expect:

a) to learn efficient methods to represent and store `natural language’ data;
b) to familiarise with the latest developments in the area of semantic and topic modelling;
c) to mobilise natural language processing algorithms in the context of deep learning frameworks (e.g., Google’s Tensor Flow library).
Regression Analysis
Students and practitioners in the area of business analytics need to undertake empirical research. This module introduces you to the fundamental concepts of econometrics and its usefulness in analysing business and financial data.

It is designed to give you an understanding of why econometrics is necessary, to provide you with a working knowledge of basic econometric tools, to introduce you to an econometric and data science software and to illustrate their application in business.
Supervised Machine Learning
This module provides a comprehensive overview of supervised learning techniques, which aim to mine valuable information between the predictors and the response and train models to make accurate prediction.

You should expect to learn a variety of supervised learning techniques and have hands-on experience to apply those techniques to tasks in the business world, such as fraud detection and credit scoring.
Predictive Analytics Knowledge Integration
The main aim of the module is to train the students with the necessary skills to identify actionable insights from data by appealing to a variety of analytics tools.

Knowledge of previously taught methodologies for basic development purposes are combined and integrated with one business goal, and illustrations are made through use cases.

The skills trained within this module prepare the students for further training offered by our programme, especially the specialised knowledge integration modules and personalised industry projects.
Scalable Analytics Methods
This module provides a comprehensive foundation in scalable analytics methods, preparing you to tackle the complexities of massive data and empowering them to contribute effectively to data-driven decision-making in business.

You should expect to learn a variety of scalable data analytics methods for massive data and have hands-on experience of handling massive data to solve real-world business problems through scalable platforms such as Spark and high-performance computing (HPC) clusters.
Frontiers of Business Analytics
This knowledge integration module deals with creating full stack business analytics projects.

Mainly, the attention revolves around designing and implementing complex data pipelines, i.e., pipelines comprising pre-processing, transformation, analysis, and visualisation tasks with economic and financial data.

Further, this module is applied since students must bridge the notions and tools acquired in disparate modules to address real-world problems.
Deep Learning
Deep learning has become the most important subset of machine learning methods, relying on sophisticated methods to analyse complex and often unstructured data, such as images, or natural language.

In this module, you will learn about essential deep learning tools and how to apply them in a range of business contexts.

Core modules

Data Management Systems
This module focuses on modern data management frameworks and tools for getting, storing, and deploying massive datasets.

In particular, you should expect to familiarise yourself with two top-notch database management systems and leverage these to manipulate massive datasets in the context of key data management tasks.

This module also provides Postgres and MongoDB training, and Postgres and MongoDB Bootcamps are scheduled.
AI-Powered Analytics
To carry out state-of-the-art analytics, businesses increasingly rely on advanced AI tools and platforms, such as powerful data exploration systems, machine learning workflow platforms, or large language models.

This module seeks to bridge the gap between conventional business analytics and the transformative power of AI, introducing students to emerging tools and their application in a range of business contexts.

This module also provides Power BI training, and a Power BI Bootcamp is scheduled.
Consulting Research Methods for Business Analytics
In their applied research project and in their future work roles, students are expected to systematically apply a range of analytics tools to answer complex research questions.

This module aims to build the relevant skills to conduct data-driven research projects, by providing the methodological foundations and providing the space to practice them in real business contexts.
Explainability of Analytics Methods
Business analysts are often asked to explain machine learning and statistical learning solutions to end-users and decisions-makers that rely on such business solutions.

This module shows you how to use explainability to overcome the black-box effect of complex models that are usually deployed at the expense of reduced interpretability.
Network Analytics
This module provides you with an overview of a range of 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).

This module provides students with cutting-edge network theories and practical tools to appreciate the organisation and functioning of disparate networks.

Ultimately, the goal is to develop a distinctive angle on how networks bring value to individuals, organisations, and communities.
Embedding Innovation
Once innovators (startup entrepreneurs or corporate employees) have developed an idea for a new product or service, they need to take a critical step: convincing key stakeholders, such as their managers and potential customers, of the added value of the innovation.

In this module, you will learn the methods and strategies innovators use to get support for different types of innovation, in a variety of contexts.

Elective Modules

Final Year Applied Research Project
The Applied Research Project aims to provide a link between the various subjects studied in the degree, while encouraging the production of independent industry-lead research.

It is a vital and substantial part of the final year of your degree as it serves as a basis of discussion with prospective employers.

Industry sponsored projects will be provided to you, and you will decide which specific project and industry partner will be more suitable to your professional development.
Spatial Analytics
The main aim of the module is to train the students with the necessary skills to identify actionable insights from observational data by appealing to a variety of spatial analytics tools.

The skills trained within this module help the students to extend their skill portfolio by having practical experience with deploying spatial data analytics.
Business in Society
This will give you an appreciation of the role of business within society as a whole.

You will learn about broader ethical issues and the connections between businesses and a wide range of stakeholders.

You will also discuss the purpose of businesses and how they relate to external factors.

You will study the demands, expectations, and potential conflicts that result from these factors.
Micro-placements
The module seeks to enhance career exploration and will provide you with professional level experience in the form of a self-contained project with one of our external employer partners.

Your Micro-Placement project will last for four weeks and will take place from June, once your second-year finishes.

This elective will introduce you to a series of competencies and employability skills that will enhance your career readiness. It will also raise your awareness of the diversity of career options following your degree.
Summer Internship
The module seeks to enhance career exploration and will provide you with professional level experience in the form of a self-contained project with one of our external employer partners.

Your Micro-Placement project will take place from June, once your second-year finishes.

This experience will help you explore different career options, helping you to be more confident in deciding whether this career option is right for you and give you valuable professional work experience for your CV.
Network Analytics
This module provides you with an overview of a range of 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).

This module provides students with cutting-edge network theories and practical tools to appreciate the organisation and functioning of disparate networks.

Ultimately, the goal is to develop a distinctive angle on how networks bring value to individuals, organisations, and communities.
Change Management
This module aims to give you both a theoretical and practical understanding of the issues involved in change management.

It emphasises the need for the use of context sensitive approaches to change in organisations.

By the end of the module, you should be capable of putting your theoretical knowledge into practice within an organisation.
Behavioural Decision Making
This module will introduce you to some of the main ideas, frameworks and tools developed by decision-making researchers (e.g., behavioural economists, psychologists of judgement and decision making).

The module will examine how individuals (e.g., managers, consumers, investors, entrepreneurs) and groups of individuals (e.g., teams) make decisions.

It will cover both descriptive and prescriptive models of decision making.
The Role of Environmental, Social and Governance in Banking and Finance
ESG (Environmental – Social – Governance) has become a familiar phrase over the last years, but what is its significance in relation to finance?

The financial ecosystem has a key role to play in solving the environmental crisis and it can only do so with a strong basis of governance and social values in place.

The core aim of this module is to shed light on the relationship between the economy/finance and climate change as well as the importance of social and governance-related drivers in this space.

Through all core modules you will develop the Graduate Attributes, five core skillsets that will help you launch a successful, fulfilling career. Find out more about the Graduate Attributes.

Download course specification:

Business Analytics BSc (Hons) [PDF]

Assessment methods

Examinations
Course work
Presentation
Tests

Term dates

Academic year

For a full breakdown of the current and forthcoming academic year view our term dates page.

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Careers

The Business Analytics course provides a solid foundation for those that would like to pursue a career where data-based decision making, technology and analytics skills are essential differentiators.

The course is not sector specific, and graduates of this course are employed across a broad range of professions and industries.

Graduates of the BSc Business Analytics are equipped with knowledge and skills that will enable to begin a career in various areas that requires data-led decision-making and analytics skills such as analytics consultancy, audit/financial/fraud/investment analysis, business analysis, business intelligence, data analysis, data insight generation, data science, data technology, digital marketing, market research, marketing consultancy, policy analysis, (geo)political analysis, product management, product development, social media analysis, technology analysis/consultancy, etc.

Alumni stories

Hear from our alumni. Discover the real experiences of learning at Bayes and how Bayes helped to boost our graduates' careers.

Read all stories

Placements

This additional year is credited and will count 10% towards your degree classification. It is a recognised part of the degree programme and will be endorsed on your final degree certificate.

Fees & funding

UK/Home fee

Tuition fee for September 2026

Full-time BSc tuition fee:

£9,790 per year

^* Tuition fees are subject to annual change.

International fee

Tuition fee for September 2026

Full-time BSc tuition fee:

£28,000 per year

^* Tuition fees are subject to annual change.

Tuition fee increases

Our undergraduate fee for UK students in 2026/27 is £9,790 for the first year of study in line with the Government policy. The fee for each subsequent year of study may also increase in line with government policy and we will confirm any such increase with you directly as and when the fee is confirmed.

Scholarships & bursaries

Funding

There are a variety of funding options for all levels of study, including loans, grants and scholarships. Find out more about funding and financing your time at City St George's here.

Each year, Bayes Business School, City St George's, University of London and generous donors create opportunities for students to fully fund or part fund their studies. Find out more about scholarships and loans

Fee waivers may be available for this course
Means tested support may be available for 2026/27 entry. Find out more about undergraduate funding.

View our scholarships and funding

Entry requirements

Standard home offer

A LEVEL

A (Maths) AA

Grade 4 (C) in GCSE English Language or English Literature.
IB

35 points

overall, with minimum 6 in Higher Level Maths and either Higher Level 4 or Standard Level 5 in English.
BTEC

DD

Plus A Level Maths grade A and GCSE English Language or English Literature grade 4 (C)

UK qualifications

A Level: A (Maths) AA

We accept all foreign language A Level subjects, and such subjects are considered for entry even if it is the applicant’s native language.

If you are studying General Studies or Critical Thinking these subjects will not be included in any offer condition.

For A-Level applicants we also require a minimum of grade 4 (C) in GCSE English Language or English Literature.

BTEC: DDD

Plus A Level Maths grade A and GCSE English Language grade 4 (C).

OCR Cambridge Technical Level 3 Extended Diploma: DDD

For OCR Cambridge Technical applicants we also require A Level Maths grade A and a minimum of grade 4 (C) in GCSE GCSE English Language or English Literature.

Cambridge Pre-U: D3 D3 D3 (including Maths)

Plus grade 4 (C) in GCSE English Language.

For candidates taking a combination of A Level/BTEC/OCR Cambridge Technical qualifications we accept the following:

BTEC/OCR Cambridge Technical Level 3 National Diploma (grades DD) with A-Level Maths A
BTEC/OCR Cambridge Technical Level 3 Subsidiary Diploma/National Extended Certificate (grade D) with two A-levels (including A-Level Maths A and a second A-Level grade A)

For combination BTEC/OCR/A-Level applicants we also require a minimum of grade 4 (C) in GCSE English Language or English Literature.

IB: 35 points overall, with minimum 6 in Higher Level Maths and either Higher Level 4 or Standard Level 5 in English. Please note that we are happy to accept both Maths Analysis & Approaches and Maths Applications & Interpretations.

International Baccalaureate Career-Related Programme – We welcome IBCP applicants on a case-by-case basis.

Access to Higher Education: Pass the course with 45 Level 3 credits which includes a minimum of 30 credits at Distinction level with the remaining 15 credits at Merit or above. In addition to this, all applicants are required to have A Level Mathematics grade A.

For Access applicants we also require a minimum of grade 4 (C) in GCSE English Language or English Literature.

T Levels: Distinction plus A Level Maths grade A and GCSE English Language or English Literature grade 4 (C)

Bayes accepts all T Level pathways

Contextual admissions

We apply a contextual admissions process for UK undergraduate applicants who have been in care, attend a low performing school, live in an area where few students go to university, or are the first generation of their family to enter Higher Education.

Those who are eligible may receive a conditional offer with reduced entry requirements, typically up to two grades lower for A-levels and one grade for the International Baccalaureate Diploma.

International qualifications

Below is a list of countries and regions, with information on the qualifications we accept for each.

English language requirements

Information for international and EU applicants

For international applicants requiring a Student Route visa we accept any of the below English language proficiency qualifications at the grades listed.

Please note, the Official Certificate must be awarded OR the qualification must be verifiable online. Statement of Results willnotbe accepted.

English tests need to have been taken no longer than two years from the date that the CAS is generated.

English Language Tests:

IELTS (Academic, UKVI or IELTS Indicator): 6.5 overall with no less than 6.0 in any sub test
IELTS One Skill Retake: Must be taken within 60 days of previous IELTS test. Accepted for one sub test where all other components and the overall score have been met
Language Cert International Academic ESOL: 70 overall and 70 in each component
Language Cert International ESOL: B2 Communicator (101 Listening, 38 Speaking, 101 Reading, 101 Writing)
TOEFL (Test centre or iBT Special Home Edition) – new criteria: 4.5 overall (4.5 minimum in each sub test)
TOEFL (Test centre or iBT Special Home Edition) – old criteria: 90 overall (21 Writing, 23 Reading, 23 Speaking, 21 Listening)
Pearson Test of English (PTE) Academic: 62 overall with minimum of 62 in each sub test
Cambridge English Advanced (also known as Certificate in Advanced English): Grade C with 176 overall and minimum 176 in each component
Cambridge English Proficiency (also known as Certificate of Proficiency in English): Pass qualification (all grades accepted)
Oxford Test of English 140 overall with minimum 140 in each sub test
Singapore Cambridge O Level: Grade C or above.

English Language Qualifications:

IGCSE English as a First Language (Syllabus 0500 & 0522): Grade C / 5 or above
IGCSE English as Second Language (Syllabus 0510 & 0511): Grade B/ 6 or above
International Baccalaureate: Grade 5 at Standard level or Grade 4 at Higher level
Trinity College (Integrated Skills): Distinction ISE II – pass in each area
City St George’s International Study Centre Pre-sessional English: 6.5 overall with no less than 6.0 in any sub test (NB. Must be the 6 or 8 week Bayes-specific course)
Hong Kong Diploma of Secondary Education (HKDSE): English Language Examination grade 4 or above
GCSE English Language Grade C/5 or above but 1) Qualifications must be issued by Ofqual, SQA, Qualifications Wales or CCEA regulated body in the UK; 2) Education must be undertaken in a UK school
A Level English Language/English Literature: Grade C or above
Vitnemal English grade 5
French Baccalaureat: 14/20 in English
Malaysian GCE O Level (SPM-1119 syllabus only): grade A.
Malaysian Certificate of Education (Sijil Pelajaran Malaysia): C+
WAEC (West African Examinations Council: C5 (from 2015 onwards)
Oxford Digital English Language Test (Digital & In person): Score 7 with at least 6 in all skills.
CaMLA/EPCE: score of 650 (low pass)
All India School Certificate Examination English (CBSE and ISC boards only): 70%

An exception to the above criteria applies to Student Route visa applicants from the below majority English-speaking countries for whom we can accept a wider range of English qualifications:

Antigua and Barbuda
Australia
The Bahamas
Barbados
Belize
Canada
Dominica
Grenada
Guyana
Ireland
Jamaica
Malta
New Zealand
St Kitts and Nevis
St Lucia
St Vincent and the Grenadines
Trinidad and Tobago
United Kingdom
United States of America.

Don’t meet the English language requirements? City St George’s International Study Centre offers English language programmes to help prepare you for study at university.

This intensive and flexible course is designed to improve your English ability for entry to degree courses:

Online Pre-sessional English.

Information for home applicants

In addition to the above English language proficiency qualifications accepted for International applicants, as a Home or EU applicant we can also accept any of the below English qualifications:

GCSE: Grade C or 4
O-Level: Grade C
A-Level: Grade C
Cambridge English First (also known as Certificate of First in English): Grade A (180-190) at CEFR Level C1.

Foundation and preparatory courses

UK students

If you do not meet the qualification criteria for this course, you may still meet the criteria for our Actuarial Science Foundation course. The Foundation course is a one-year full-time programme that provides an entry route to the BSc Actuarial Science course.

Foundation courses for International students

Don’t meet our entry requirements? Study a international foundation course with one of our two partner institutions. These courses are specifically designed for international students who do not meet our required academic and English language requirements for direct entry.

They help prepare you for study at City St Georges and you are guaranteed a place on a specific degree at City St George’s provided you meet the progression requirements.

City St George’s International Study Centre

We have developed an International Year One Programme, specifically designed for international students who would benefit from additional academic and/or English language support. This course is jointly delivered by City St George’s International Study Centre and offers progression into the second year of the degree, subject to you meeting the required grades. More information.

City St Georges has established a purpose-built study centre near to Liverpool Street Station in the heart of London's financial district. Combining academic study with English language support, the courses at City St George’s International Study Centre provides assurance of the quality and standards of education and means you have access to a range of City St George’s services.

Find out more at: City St George’s International Study Centre

Kaplan International College London

City has a longstanding partnership with Kaplan International College London. KIC London offers fantastic teaching, support and facilities, plus a great location in the popular South Bank area of the city, close to many leading attractions.

Its courses equip students with the English language level, academic skills and key subject knowledge needed for an undergraduate degree at City St George’s.

Find out more at: Kaplan International College (KIC) London | Kaplan Pathways

Student life

Study at Bayes and take advantage of all that London has to offer - from entertainment and nightlife to West End theatres, museums and world-famous shopping districts and markets.

See our Undergraduate Student Life page for further information.

Have a question about student experience at Bayes?

Talk one-on-one with a student who is currently studying at Bayes.

Ask a student

Apply

All applications should be made through UCAS, the Universities and Colleges Admissions Service. Applications are made via Apply, UCAS's online application system.

Terms and conditions

Students applying to study at Bayes Business School are subject to City St George's, University of London's terms and conditions.

More information about applying to Bayes

Apply via UCAS

UCAS Institution code: C60 (Bayes Business School and City St George's, University of London)
UCAS Course code: N9N3

You can find more information at UCAS and in the UCAS Handbook.

Apply via UCAS | N9N3

Contact us

Speak to one of our staff from UG's programmes teams.

Business Analytics BSc (Hons)

Key information

Overview

Business Analytics BSc (Hons) Who is it for?

Why choose this course?

Course objectives

Teaching staff

Dr Jack Fosten

Course content

Course structure

Year 1

Core modules

Finance and Investment

Introduction to Management

Mathematics for Business Analytics

Data Visualisation

Business Economics

Statistics for Business Analytics

Unsupervised Machine Learning

Data Wrangling and Exploratory Data Analysis

Career Activation Programme

Year 2

Core modules

Applied Business Intelligence

Applied Natural Language Processing

Regression Analysis

Supervised Machine Learning

Predictive Analytics Knowledge Integration

Scalable Analytics Methods

Frontiers of Business Analytics

Deep Learning

Year 3

Core modules

Data Management Systems

AI-Powered Analytics

Consulting Research Methods for Business Analytics

Explainability of Analytics Methods

Network Analytics

Embedding Innovation

Elective Modules

Final Year Applied Research Project

Spatial Analytics

Business in Society

Micro-placements

Summer Internship

Network Analytics

Change Management

Behavioural Decision Making

The Role of Environmental, Social and Governance in Banking and Finance

Download course specification:

Assessment methods

Term dates

Academic year

Careers

Alumni stories

Placements

Fees & funding

UK/Home fee

Tuition fee for September 2026

International fee

Tuition fee for September 2026

Tuition fee increases

Scholarships & bursaries

Funding

Entry requirements

Standard home offer

UK qualifications

Contextual admissions

International qualifications

Australia

Austria

Belgium

Bulgaria

Canada

China

Croatia

Cyprus

Czech Republic

Denmark

Estonia