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Students
Tuition Fee
GBP 9,500
Per year
Start Date
2025-09-15
Medium of studying
On campus
Duration
12 months
Program Facts
Program Details
Degree
Masters
Major
Artificial Intelligence | Data Analytics | Data Science
Area of study
Information and Communication Technologies
Education type
On campus
Timing
Full time
Course Language
English
Tuition Fee
Average International Tuition Fee
GBP 9,500
Intakes
Program start dateApplication deadline
2025-09-15-
2026-01-19-
About Program

Program Overview


Data Science MSc

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

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.


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.

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 bachelor's degree (3 years) | 2:2 classification

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 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.


Fees and finance

  • 2025/26 fees are:
    • £9,500 if you're from the UK/Europe
    • £17,000 if you are an international student

If you're unsure whether you qualify as a UK, EU, or international student, find out more in our Help and Advice article.


See the scholarships and bursaries that may be available to you.


This information was correct at the time of publication.


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.


Program Outline

MSc Data Science at the University of Sunderland: A Comprehensive Overview


Degree Overview:

The MSc Data Science program at the University of Sunderland is designed to equip students with the knowledge and skills to work in the growing field of data science. The program aims to train students to understand different data types, fuse diverse datasets, utilize advanced analytics methods, and present data insights effectively. This program is ideal for individuals with computing, STEM backgrounds, or prior experience in data analysis. It focuses on developing students' abilities to solve real-world problems using data-driven approaches.


Outline:

The program comprises numerous modules covering various aspects of data science, including fundamental concepts, programming techniques, machine learning, and data analytics. Notably, it employs a balanced set of teaching and learning methods including lectures, group work, research, seminars, tutorials, and practical laboratory sessions.


Core Modules:

  • Data Science Fundamentals (30 credits): This module delves into various data types, fusion techniques, analytical tools, and presentation methods.
  • Data Science Product Development (30 credits): Students learn to design and develop data science products to address real-world challenges, conduct systematic literature reviews, and build prototypes.
  • Machine Learning and Data Analytics (30 credits): This module equips students with theoretical and practical knowledge in machine learning, data mining, and data analytics.
  • Technology Management for Organisations (30 credits): This module focuses on cybersecurity and data science applications in organizations, covering risk mitigation, resilient solutions, and governance aspects.
  • Computing Masters Project (60 credits): Students delve into a specific research area, develop a deliverable, and conduct a thorough literature review to underpin their project.

Assessment:

Assessments in this program are entirely coursework-based, with no exams. Methods include writing reports, research papers, completing practical assignments, and undertaking a final project.


Teaching:

The program is delivered by an enthusiastic teaching team supported by the Academic Technical Support team. The latter assists students with practical sessions, projects, and configuration of equipment. Additionally, the program boasts state-of-the-art facilities, including specialized computing labs and high-performance computing platforms.


Careers:

This program prepares graduates for diverse career paths in data science, with opportunities in government agencies, high-tech companies, consulting firms, and market research organizations. Upon completion, graduates are equipped to progress in attractive fields and industries.


Other:

The program emphasizes the increasing demand for data scientists, highlighting it as one of the highest-paid jobs in the computing field.


Important note:

Admission requirements, fees, and application process details are not included in this comprehensive overview.


Additional Information:

  • The program requires a 2:2 or above in a computing or related discipline (mathematics, statistics, engineering) or a 2:1 or above in a relevant non-computing discipline with numeracy or big data as a significant theme.
  • International students can benefit from the European student fee scholarship for the 2024/25 intake.

Contact:

For further information or inquiries, contact the Student Helpline at 0191 515 3000 or email student.helpline@sunderland.ac.uk.


Tuition Fees and Payment Information:

  • UK/Europe: £8,500
  • International: £16,500
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Admission Requirements

Entry Requirements:


For UK/EU Applicants:

  • A 2:2 or above in a computing or related discipline (mathematics, statistics, engineering)
  • OR a 2:1 or above in a relevant non-computing or related discipline (which includes numeracy and/or application of big data as a significant theme).
  • English language proficiency (for non-native speakers, see below)

For International Applicants (Outside the EU):

  • A minimum GPA of 2.40 for a Canadian bachelor's degree
  • A minimum GPA of 2.5 for a USA bachelor's degree
  • English language proficiency (see below)

Additional Notes:

  • If you already hold a postgraduate qualification, please refer to the Applying for additional postgraduate degrees Help and Advice article.
  • If your qualification is not listed above, please contact the Student Administration team for further advice.
  • If you don't meet the standard entry requirements, you can take one of the foundation pathways at our partners ONCAMPUS Sunderland.

Language Proficiency Requirements:

  • For non-native English speakers, an IELTS score of 6.5 with a minimum of 5.5 in each component is required.
  • Other equivalent English language qualifications may be accepted.
  • Please contact the university for more information. ## Summary: To be eligible for the MSc Data Science program at the University of Sunderland, applicants need to meet the following entry requirements:
  • UK/EU Applicants:
  • A 2:2 or above in a computing or related field, or
  • A 2:1 or above in a non-computing field with relevant elements
  • English language proficiency
  • International Applicants:
  • A Canadian bachelor's degree with a GPA of 2.40 or above, or
  • A USA bachelor's degree with a GPA of 2.5 or above
  • English language proficiency
  • For more details, please refer to the university website or contact the admissions team.
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