Data Analytics MSc (PGCert PGDip)

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We can help you meet our English language or academic entry requirements.

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Top reasons to choose this course

• Work in collaboration with external partners, such as banking institutions, energy companies, NHS, using real data sets to prepare you for work.
• Placement opportunity to gain work experience and make valuable contacts. 
• Guest speakers from industry delivering seminars and workshops
• Work with data examples of real applications covering examples in data mining, data science life cycle, Big Data, AI, financial data, health data, credit risk, and customer base analysis. 
• Access to computer labs with specialist software including SAS, SPSS, SPSS Modeller, R, RStudio. 
• By undertaking the Programming for Analytics with SAS option module you are eligible for SAS Specialisation (SAS Joint Certificate), with evidence of SAS skills in your final project. 

Our mathematics department has SAS Academy status. SAS is one of the largest providers of business analytics software in the world. Academy status gives our students the opportunity to meet SAS customers and their industry partners at careers fairs, to train in skills needed by a wide range of companies and organisations, and to be prepared for SAS certification exams. 

Syllabus

The course covers three main areas:

• data management – structuring and manipulating data for analysis purposes
• data interpretation – statistical analysis using advanced features of industry-standard software such as SAS, R, Python and SQL.
• project management – the business-specific and strategic aspects of analytics.

You will study five core modules. One of these involves a major project, potentially in collaboration with industry. You will also choose option modules allowing you to focus on particular areas of interest.

Modules

Core modules

• Data Management

  Databases form the underlying framework of information systems in businesses and organisations, and this module will equip you with an understanding of contemporary database management systems. It also provides you with a methodology for database design and development, as well as skills in searching, reporting and analysing the data.

• Business Analytics Strategy and Practice

  Data analytics is inextricably linked to business strategy, and this module will introduce you to a variety of business and management concepts including leadership, change, team working and project planning. You will also explore analytical aspects of business goals, business knowledge and business evaluation and how to effectively apply analytical results.

• Introduction to Statistical Data Analysis with R

  This module will teach you the basics of statistics and computer programming needed for data analysis. You will use R to run computer simulations and explore random processes. You'll use what you've learned during the module to complete a realistic data analysis project.

• Data Mining and Knowledge Discovery in Data

  In this module you will study a range of data analysis and machine learning methods for turning raw data into useful information and knowledge that provides a solid basis for operational and other decisions arising within different professional situations. You will learn how these methods work and how to select the most appropriate ones to find useful and relevant patterns, trends and anomalies in data sets.

• Project

  During this module you will undertake a major analytics project involving researching patterns and trends in data that provide business information and knowledge. The data research enables you to use the concepts and methods learned from previous modules and provides you with the opportunity to demonstrate self-planning, self-study, initiative and motivation. Most research projects will be industrially based using real data sets.

Options*

• Multivariate Analysis and Statistical Modelling

  Building on your prior knowledge of probability and statistics, including the use of software for statistical analysis, this module will provide you with the capability to design statistical experiments, analyse multivariate data and apply statistical modelling techniques in practical scenarios. It will enable you to enhance your skills in using specialist software of your choice.

• Medical Statistics

  The module is concerned with the application of statistical concepts, models and techniques to analyse, compare and evaluate the data from medical studies. The skills you develop here will be applicable to other similar studies in scientific and business contexts. Topics include analysis of longitudinal studies; survival analysis; sample size calculation; and regression analysis.

• Programming for Analytics with SAS

  You will enhance your skills in computer programming using SAS software in the context of data analytics during this module, which features teaching materials developed with industry-leading experts in statistics and analytics from the SAS Institute. The goal is to build sufficient SAS programming skills and understanding of statistical concepts to complete a major data analysis project.

• Forecasting and Credit Risk Analysis

  This module provides an introduction to the statistical methods used to estimate risk and reward in retail credit, with a particular focus on credit risk and credit score models for application of loans. It will also provide you with an understanding of forecasting methods and their application, using examples from areas such as economic and marketing time series.

*Option modules are indicative and may change, depending on timetabling and staff availability.

Placement year

To further increase your employability and international experience we offer full-time students starting in September the opportunity to take a placement year. This means that your course will take two years, but you’ll be graduating with work experience.

The year on placement in a role related to your course will allow you to put all that you have learned on your masters into practice, enhancing your career opportunities and giving you practical experience in your area of expertise.

The placement is assessed formatively throughout the year, giving you the chance to reflect on your experience and helping to build your CV.

Work placements are optional, and you'll arrange your placement with support from our dedicated Placements and Employability team.

We offer a two-year international study visa route to support applications for this course.

Student projects 

Examples of student projects include:

• Predicting patterns in relation to data involved in mobile gaming

• Factors affecting visitor behaviour and visitor numbers to the Royal Pavilion, Brighton

• The effects of Tommy John surgery on major league baseball pitchers

• Automatic classification of students’ free-text responses in NSS and BSS surveys

Meet the team

Dr Sonia Timoteo Inacio, course leader

I began my career in applied mathematics, completing a PhD in Statistics and Risk Management before spending nearly 15 years in industry. From credit risk modelling in financial institutions to market research with companies like Nielsen, I gained extensive experience in real-world data analysis. In 2015, I joined the University of Brighton, drawn by its vibrant and collaborative academic environment.

My passion for teaching began early, during a one-year teaching post after my degree. The dynamic classroom environment and the opportunity to help students grow in confidence and skills stayed with me. Returning to academia felt like a natural step, bringing industry insight into my teaching.

As course leader for the Data Analytics MSc, I focus on employability and professional readiness. I’ve developed modules in areas like Credit Risk, Forecasting, and Programming, ensuring students gain practical, up-to-date skills. I also lead partnerships with external organisations, offering students the chance to work on real-world projects. I’m especially proud of our long-term collaboration with the SAS Institute, embedding professional certification into the course.

Analytics is central to addressing global issues—from healthcare to sustainability. I encourage students to stay curious, think critically, and be storytellers with data. Seeing them grow into confident professionals, some securing jobs before graduation, is the most rewarding part of my role.

Course fees

Scholarships, bursaries and loans

We offer a range of scholarships for postgraduate students. Bursaries and loans may also be available to you.

Find out more about postgraduate fees and funding.

The fees listed here are for the first year of full-time study if you start your course in the academic year 2025–26.

You will pay fees for each year of your course. Some fees may increase each year.

UK undergraduate and some postgraduate fees are regulated by the UK government and increases will not be more than the maximum amount allowed. Course fees that are not regulated may increase each year by up to 5% or RPI (whichever is higher).

If you are studying part-time your fee will usually be calculated based on the number of modules that you take.

Find out more

• Fees, bursaries, scholarships and government funding info for UK and international postgraduate students
• Student finance and budgeting while studying
• About the university’s fees by checking our student contract and tuition fee policy (pdf).

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