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MSc Data Science and Artificial Intelligence

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RS2725 Open Day (5) (2)
Institution code: 

One year full-time.

Two years part-time.

September intake each year.

Typical Offer: 

2:2 or above in an undergraduate degree.

Please see Entry Requirements below.


The MSc Data Science and Artificial Intelligence is a postgraduate conversion degree. It is a partnership between us and you – we will give you the opportunities to gain deep knowledge, practical skills and meaningful expertise in data science and artificial intelligence, you bring enthusiasm, determination and a willingness to learn and make the most of the opportunities.

This is a conversion course so your undergraduate degree can be in any subject.

Course modules

Full downloadable information regarding all University of Suffolk courses, including Key Facts, Course Aims, Course Structure and Assessment, is available in the Definitive Course Record.

Introduction to Artificial Intelligence (Requisite)

This module provides an introduction to the artificial intelligence field, covering the history of the discipline and exploring the breadth of the discipline from “classical AI” to the current forefront areas. It provides a grounding in how to undertake research in AI and data science, and considers ethical issues arising in AI and data science applications

Python Programming for AI and Data Science (Requisite)

Programming is a core skill throughout computing. This module will cover Python programming with particular emphasis on using Python to solve problems with AI and data science techniques. No programming experience will be assumed. The module will begin with the key elements of Python programming and build towards harnessing the standard Python libraries and packages to create solutions. Best practices of Python coding will be embedded throughout the module. The module will also provide a primer on software engineering of solutions, with an emphasis on the importance of testing. 

SQL and NoSQL Databases (Requisite)

Industry, commerce and research are being transformed by the potential to capture, store, manipulate, analyse and visualise data and information on a massive scale. Relational (SQL) databases and data warehouses remain important repositories of information to many organisations. The advent of Big Data with its variety, velocity and volume has challenged relational databases, leading to the emergence of NoSQL databases. Yet the query languages of NoSQL databases have evolved closer to SQL capabilities. This module will cover both SQL and NoSQL approaches to data modelling, database design and manipulation, so that you can use the right tool for the right job.

Data Mining and Statistical AI (Requisite)

Data science and artificial intelligence includes many techniques for classification, analysis and prediction. This module focuses on those techniques relating to data mining and statistically driven approaches, providing you with an arsenal of methods to solve business problems and generate real insights.

Deep Learning Techniques and Tools (Requisite)

Deep learning is central to modern AI. A sufficiency of inexpensive computing power, sufficiently large datasets and a number of key theoretical advances created deep learning techniques which have facilitated a wave of accuracy increases across many computational tasks (computer vision, natural language processing, speech recognition, autonomous driving, etc.), making many applications practical. This module explains the underlying mathematics and techniques, so that you can master deep learning and solve real problems.  

Cloud Computing for AI and Data Science (Requisite)

The on-demand delivery of compute, database, storage, applications and IT resources through cloud computing has enabled many organisations to deliver innovative solutions without upfront capital investment. Cloud computing ecosystems provide a variety of scalable AI and machine learning solutions. This module provides a comprehensive grounding in cloud computing concepts and solutions, buttressed with extensive practicals to build experience in individual services and architectural designs. As the University of Suffolk is an AWS Academy partner institution, the module will give you an opportunity to acquire AWS certification(s) if you so wish. 

Extended Project (Mandatory)

The Extended Project is the culmination of the MSc Data Science and Artificial Intelligence conversion degree. This project is your opportunity to apply the knowledge and skills acquired from all the earlier modules on a real task – it is very likely a project proposed by a company or research organisation. 

Career opportunities

Employer demand for people skilled in Data Science and AI is proven. The number of AI jobs in the UK listed on its online jobs board grew 485% between 2014 and 2017 according to research from the job website ‘Indeed’. Gartner’s survey on AI revealed that there is a rapid growth in the number of AI based jobs in big organisations, and a tempo change from 4 projects per organisation in 2019 to 10 projects in 2020 and accelerating to an expected 35 projects in 2022.  
Regionally digital skills in general and Data Science in particular have been identified by employers as a priority area. The Innovation Martlesham cluster where the University of Suffolk’s new DigiTech Centre is co-located has seen growth in the number of ICT jobs from 600 in 2016 to 1200 in 2019 with 2000 jobs projected for 2023.

An increasing percentage of these jobs require core skills in Data Science and AI. Consultations with regional businesses revealed that there is an increasing demand for professionals with strong Data Science skills who are capable of developing machine learning models based on existing AI rapid development frameworks. As a graduate of this degree, you will be ideally placed to take advantage. 
In addition to careers in industry, as a graduate of this course, you will also be able to progress into doctoral research. 

Read about what it's like to work at Adastral Park

Student profiles


MSc Data Science and Artificial Intelligence Student

MSc Data Science and Artificial Intelligence Student

MSc Data Science and Artificial Intelligence Student

Fees and finance


  • UK full-time tuition fee: £8,748 p.a
  • UK part-time tuition fee: £972 per 20 credits (please contact the Student Centre for further information)
  • International full-time tuition fee: £13,995 p.a

Further Information


At the University of Suffolk, your tuition fees provide access to all the usual teaching and learning facilities that you would expect. However, there may be additional costs associated with your course that you will need to budget for.

Entry requirements


Professor of Information Systems Engineering

Lecturer and Course Leader for Data Science and Artificial Intelligence

Facilities and Resources

Teaching is intended to take place in the DigiTech Centre at Adastral Park, which was unveiled by Her Royal Highness the Princess Royal on 12th November 2019. A collaboration between University of Suffolk and BT, with funding from the New Anglia Local Enterprise Partnership (LEP), it has been established to provide training in cutting-edge digital skills for people looking to pursue careers in the nationally-important information and communications technology (ICT) sector, as well as fuelling high tech businesses who increasingly require access to a talented technology workforce.

The centre will form part of the growing ‘Innovation Martlesham’ technology cluster at Adastral Park, home of the globally recognised BT Labs and more than 130 companies ranging from start-ups to multinational corporations such as Microsoft, Tech Mahindra and Cisco.

Nearly ten million pounds of investment is going into remodelling existing buildings, purchasing specialist equipment and creating a number of high-end labs. These include: Data Science and Artificial Intelligence (AI) Laboratory; Smart Systems living lab; Cyber Range (Digital forensics and cyber security); Visualisation, gamification and immersive environments. These labs and three new IT suites will be accessible remotely from the Waterfront Building and the Atrium Building in the Waterfront campus and elsewhere.