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.
Introduction to Artificial Intelligence (Requisite)ю 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 include 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 computing, 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.
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.
Fees and finance
Full-time tuition fee: £8,235
Part-time tuition fee: £915 per 20 credits
International tuition fee: £12,150
20% reduction in fees for University of Suffolk graduates
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.
Applicants are expected to hold an undergraduate degree of 2:2 or higher.
Applicants may be expected to attend an interview as part of the application process.
English Language Requirements
IELTS (Academic or UKVI): 6.5 overall, and a minimum of 5.5 in each component
Cambridge Assessment English: C1 Advanced Certificate in Advanced English minimum overall score of 180, no less than 162 in each component
Pearson Test of English (PTE Academic): CEFR C1 Level
TESA (Test of English for Studies Abroad): 6.5 overall, and a minimum of 5.5 in each component
TOEFL iBT (only acceptable for students who do not require a Tier 4 visa to study in the UK): 93 overall with a minimum of 12 in reading, 11 in listening, 17 in speaking and 20 in writing
University of Suffolk Password Skills Test: 6.5/7.0 overall, and a minimum of 5.5 in each component