Data Science MSc (CID1258)




University of Sunderland

Data Science MSc

Course overview 

This newly developed Data Science course will provide you with the technical and practical skills to analyse big data that is key to success in future business, digital media and science. Study industry-specific topics and specialise in areas such as data mining, machine learning, data analytics and visualisation, and security of big data.

Our close links to industry and businesses in the North East, as well as the research expertise of our academics, makes this course unique and ensures that the course structure is developed according to the needs of the employment sector.


Why us?

  • The digital sector will require 300,000 new recruits by 2020, according to the UK commission for Employment and Skills, 2013
  • The department has been a Cisco partner for over 10 years 

Modular 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 methods include written reports and research papers, practical assignments and the Masters project.

Research Skills and Academic Literacy (15 credits)

Gain an understanding of research methods, including qualitative and quantitative approaches and learn how to write a technical paper. Carry out literature surveys, data collection, critical evaluation and appraisal of published work and data sets.

Big Data in Organisations (15 credits)

Explore the principles of data science in order to determine the benefits of utilising big data sets in organisational settings. Develop techniques and use tools that will enable you to undertake critical analytics of the challenges and opportunities of using big data sets in context.

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.

Data Visualisation (15 credits)

Discover the challenges of big data analysis from a visualisation perspective and examine trends in big data visualisation. Learn the principles of data visualisation, the cycle of visualisation and visualisation workflow and the risks involved in big data visualisation, including: misrepresentation and misunderstanding.

Machine Learning and Data Mining (15 credits)

Prepare yourself for the challenges of big data in pattern extraction and knowledge discovery, and gain an understanding of machine learning and data mining technologies.

Data Analytics (15 credits)

Examine the feature of data warehouses and understand how they are designed, developed, implemented and maintained, as well as what role they play in the support of data analytics.

Big Data Security (15 credits)

Analyse the range of trade-offs in balancing the security properties of confidentiality, integrity and availability and the usability demands of big data. Learn how to manage concepts of risk, threats, vulnerabilities and potential attacks in the context of big data.

Master Project (60 credits)

Carry out a real-world research project in the domains of data science, big data and open data. Receive support from a sponsor, analyse and reflect both on the research and the practical element of the project.

Fees and funding

The annual fee for this course is:

  • £4,750 if you are from the UK or EU

Questions about fees?

Contact our Student Centre on:

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