Data Science via Study Centres MSc

Apply now

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.

Register your interest

Overview

This 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.

Why us?

The college operates a significant range of training programmes for IT professionals already engaged in the industry and has extremely close ties with the Myanmar Computer Professionals Association (MCPA) and Myanmar Computer Federation (MCF)

The college has a long term relationship with Pearson/Edexel for the provision of the BTEC Higher National Diploma in Computing and Systems Development. This is an ongoing partnership which commenced in 2012

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

Course modules

Core modules:

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

This course is delivered at one of our Study Centres. Use the tab on the left to contact them directly to find out more about their facilities and location.

Entry requirements

We don’t currently display entry requirements for United States. Please contact the Student Admin team on studentadmin@sunderland.ac.uk or 0191 515 3154.

Please contact for more information on their specific requirements and equivalent qualifications from outside the UK.

Fees and finance

Please contact the study centre directly for information on fees and finance.

This information was correct at the time of publication.

Career ready

The speed at which individuals, businesses, organisations and governments are generating data is increasing at an unprecedented rate. Feedback from employers suggest that there is a significant skills gap in Data Science – there is a need for skilled professionals to make sense of the huge amount of data being generated.

Employability

The MSc in Data Science seeks to develop graduates who will become proficient data scientists with the technical knowledge base and skills set to master the complex problems and complex data requirements emanating from Big Data. The course will enable graduates to utilise the constantly changing and evolving modern technologies that continuously reshape the way digital interaction and communication takes place.

Related courses

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: 08 March 2024

We aim to provide clear, accurate and timely information to prospective and current students. We continuously review and enhance course content in consultation with our students and the information provided on our website is the latest available. If you have received an offer from us to start a course, we will communicate any important changes to you in writing. We will always seek to ensure that our prospective students are fully aware of the basis on which they are accepting an offer.