Data Science MSc

Harness new forms of data with increasingly powerful computer techniques. Gain the technical and practical skills to analyse big data. Study a unique course developed according to the needs of the employment sector.

North East Postgraduate Discount

Overview

The UK Government has identified a huge shortage of specialists in data science and artificial intelligence. The University of Sunderland is looking for a new generation of idealists, visionaries and problem solvers to help business, industry and government make the right decisions in our increasingly complex and uncertain world.

This course is designed for students who have computing, STEM experience or prior experience in working with data (e.g. statistics), to gain the knowledge and skills required to work in data science or data analytics in the real world. We are looking for people who ask questions, who don’t jump to conclusions, and who respond with caution. We want people who are able to find and communicate the best possible solutions.

On this course, you'll study subjects including the fundamentals of data science, data mining, machine learning, data analytics and visualisation, and security of big data. This highly practical course means you’ll have the opportunity to experience the latest technologies and tools used in industry, giving you the confidence to be productive and effective when you go out into the workplace.

Why us?

The course includes practical experience throughout, enabling you to transfer your new skills to industry
The course is 100% coursework-based with no exams

Sunderland boasts the second-fastest growth in digital turnover outside of London, and is the ideal city to study computing and set up a business
The department has been a Cisco partner for over 10 years

Course structure

We use a wide variety of teaching and learning methods which include lectures, group work, research, discussion groups, seminars, tutorials and practical laboratory sessions. Compared to an undergraduate course, you will find that this Masters requires a higher level of independent working.

Assessment is 100% coursework-based with no exams. Methods include written reports and research papers, practical assignments and the Masters project.

Modules on this course include:

Data Science Fundamentals (30 credits)

Learn how to use different types of data and understand how to fuse more than one dataset together. Apply a full range of traditional and intelligent analytics to a variety of datasets and make use of modern data science / big data platforms and languages. Cover techniques and tools for presenting and visualisation.

Data Science Product Development (30 credits)

Learn how to design and develop a data science product to solve a challenging real world problem, based on a systemic literature review on state of the art data science software technologies and project development methodologies, prototyping the product with end users’ evaluations. Produce a project summary report.

Machine Learning and Data Analytics (30 credits)

Study three interrelated subjects: machine learning, data mining, and data analytics including relevant professional, ethical, social and legal aspects. Focus on information and knowledge management, problems with data, approaches to selection of data analytics tools, principles of modelling and simulation, and operations research. Examine the trends, tools, and current developments in the area of machine learning, data mining and data analytics and their practical applications

Technology Management for Organisations (30 credits)

Learn to apply the principles, policies and procedures of cybersecurity and data science to provide resilient and robust organisational solutions for secure and valuable information. Develop techniques and use tools that will enable you to undertake critical analysis of the challenges and opportunities of using cybersecurity to mitigate and manage risk to data and enable business continuity in the case of data breaches. Develop a critical understanding of governance, standards, audit, assurance and review in order to evaluate the challenges in managing technology.

Computing Masters Project (60 credits)

Develop a practical deliverable and investigate an area of academic research through the support of a sponsor for example: an IT strategy; an investigative study; a technically challenging artefact (e.g. a feasibility study, design, implementation, re-engineered solution); or undertake a theoretical review based on a novel research question (provided by a research active member of staff). Underpin the project with a literature review that is a conceptual framework of your study - a systematic synthesis of concepts, assumptions, expectations, beliefs, and theories that supports and informs your research.

Some modules have prerequisites. Read more about what this means in our Help and Advice article.

Facilities

Study in a vibrant and supporting environment with state-of-the-art facilities and excellent learning resources. We are also an accredited cisco academy and have two laboratories packed with cisco networking equipment.

Entry requirements

Our typical offer is:

Qualification	Minimum grade
a Canadian bachelor's degree	GPA 2.40
a USA bachelor's degree	GPA 2.5

If you already hold a postgraduate qualification, please see our Applying for additional postgraduate degrees Help and Advice article.

If you don't meet our standard entry requirements, you can take one of the foundation pathways at our partners ONCAMPUS Sunderland. Find out more information and whether your course is eligible on our ONCAMPUS page.

If your qualification is not listed above, please contact the Student Administration team at studentadmin@sunderland.ac.uk for further advice.

We require applicants to hold an undergraduate degree with a classification of 2:2 or above in a computing or related discipline (mathematics, statistics, engineering), or 2:1 or above in a relevant non-computing or related discipline (which has numeracy included and/or application of big data as a significant theme).

If English is not your first language, please see our English language requirements.

Is your qualification not displaying here? For international qualifications, search our full list of international entry requirements for this course.

Fees and finance

Fees are:

£8,000 if you are from the UK/*Europe

Please note, applications are currently closed to international students.

*European Union (EU), EEA (European Economic Area), and Swiss nationals who do not qualify for the EU Settlement Scheme are classed as international, however, for 23/24 admission you will receive a European student fee scholarship and will pay the home tuition fee rate for the duration of your studies. The discounted fee will be reflected in your offer letter. Learn more in our Help and Advice article.

Take a look at the Your Finances section to find out about the scholarships and bursaries that may be available to you.

This information was correct at the time of publication.

The Sir Tom Cowie Campus at St Peter's by night

Career ready

Businesses and industries across the UK have identified a skills gap in data science and currently the role of a Data Scientist is one of the highest paid jobs in the computing discipline.

Employability

Progress in some of the most attractive fields and industries, including government agencies, high technology companies, consulting and market research firms. Benefit from the University’s close links with businesses and employers in the North East and join an industry-driven programme.

Related courses

MSc Cybersecurity

Contact

Contact the Student Helpline for further information about studying at the University of Sunderland:

0191 515 3000

student.helpline@sunderland.ac.uk

View Programme Specifications for the Faculty of Technology.

Page last updated: 22 September 2023

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