Postgraduate MSc/PgDip

Data Science

School of Science, Engineering and Environment





One year

Three year

Next enrolment

September 2021


In a nutshell

Make discoveries in data and bring value to businesses and organisations. With a postgraduate degree in Data Science, you can enhance your existing computing knowledge, or gain new skills that can help you secure a role in one of the fastest-growing employment fields in the digital economy.

Developed as one of the UK's first postgraduate conversion courses in this field, our BCS-accredited degree is designed to equip graduates and professionals from a wide range of disciplines and with a demonstrable mathematical aptitude, with analytical knowledge and applied programming skills.

Available with full and part-time study routes, the course provide learners with specialist data science knowledge to apply in a wide range of sectors, including healthcare, commerce, professional services and the built environment. Start dates are available each January and September.

The University of Salford is a leading regional study centre for computer science - and a great place for you to further your data science journey. We are excited to be part of the GM Cyber Foundry, the Greater Manchester city region's blueprint to be a global leader in cyber and digital research and intelligence.

You will:
  • Develop an awareness of the latest developments in advanced databases, data mining and big data tools such as Hadoop
  • Gain SAS certification while you study through our partnership with the SAS Student Academy
  • Work with real-world messy data and gain experience across the data science stack
  • Explore 'Big Data', machine learning and data visualisation

students accepted

Course accreditations
British Computing Society Accredited Degree logo

This is for you if...


You want to enhance your existing skills and qualifications for a future career in data science


You have an enquiring mind, with a practical and analytical approach to problem solving


You're a knowledge-seeker and want to learn how to tell a story with data

Course details

All about the course

The Data Science course is available in flexible study formats, including full and part-time pathways. The course comprises four 30 credit taught modules, followed by a 60 credit dissertation project. You can choose to start your studies in January or September.

  • Full-time students will take modules in trimesters one and two, and complete the project module in trimester three.
  • Part-time students will spread their studies over trimesters one and two of two years, and complete the project module in year three.

As part of study preparations, you will be required to attend an intensive one-week session before formal teaching begins. This session will review basic statistics and database concepts, and provide an overview of either Python or R programming for data analysis. 


Principles of Data Science

This module aims to provide you with the history and context of data science, the skills, challenges, and methodologies the term implies. In addition you will learn how to develop skills in presenting quantitative data using appropriate displays, tabulations and summaries, and statistical methods in developing and testing hypotheses.

Advanced Databases

This module aims to provide you with a broad overview of the general field of database systems and to develop specialised knowledge in areas that demonstrate the interaction and synergy between ongoing research and practical deployment of this field of study.

Applied Statistics and Data Mining

This module aims to introduce you to the tools and techniques to build decision making systems for business organisations; from gathering large sets of data and information, to the production of outputs and reports that will allow organisations to make strategic decisions to improve their businesses and predict future trends.

Big Data Tools and Techniques

In this module you will develop your skills and understanding of the tools and techniques available to data scientists to analyze big data. You will be able to compare and contrast how different types of developers and users can exploit Big Data platforms such as Hadoop, text analytics, Internet of Things and Social Media. Additionally, you will gain experience in data visualisation tools and techniques.

MSc Project

The project module aims to provide you with an opportunity to integrate learning from the course modules, working under the direction of an academic supervisor to carry out high-level coordinated academic and practical work on researching a suitable problem and developing, evaluating and critically assessing a robust, scalable and usable solution.

Please note that it may not be possible to deliver the full list of options every year as this will depend on factors such as how many students choose a particular option. Exact modules may also vary in order to keep content current. When accepting your offer of a place to study on this programme, you should be aware that not all optional modules will be running each year. Your tutor will be able to advise you as to the available options on or before the start of the programme. Whilst the University tries to ensure that you are able to undertake your preferred options, it cannot guarantee this.

What will I be doing?


Practical projects




Learning is delivered using a range of methods. Lectures will introduce ideas and stimulate group discussions. Tutorials will develop your ability to create problem-solving strategies and provide practice and feedback with scenarios to help with exam preparation. Workshops will develop your expertise in SAS tools, using analysis of complex datasets.

External speakers from multinational blue-chip organisations and local companies will deliver seminars to complement your learning and provide real-world case studies related to your studies.


  • 50% of the assessment will comprise a practical project where you will be given some data, conduct analysis, present your interpretations and explain your strategy.
  • 50% will comprise an examination, which will assess more theoretical aspects of the course and will assess your immediate response to unseen scenarios or data.

School of Science, Engineering and Environment

Rising to the challenge of a rapidly-changing world, our multi-disciplinary courses will shape the next generation of scientists, engineers, consultants and conservationists. Delivered by a team of dedicated academic, technical and administrative staff, you’ll experience a supportive, professional environment, where you can take your potential further. 

Learning Environment

During your studies, you will experience a modern learning environment, enriched with accessible lecture theatres and AV-equipped classrooms, computing suites and multimedia libraries, with access to industry journals, databases, and simulation software.

As a data science student, you will use computing suites equipped with software platforms and languages in machine learning, data mining, and statistical analysis. These include SAS Enterprise Guide & Miner, Python, Apache Hadoop & Spark, RapidMiner, plus NoSQL databases, such as MongoDB.

Programme Team

The Data Science postgraduate programme is delivered by an academic team with extensive industry experience and research connections.

Employment and stats

What about after uni?


Demand for data scientists outstrips supply and the is continued demand for qualified, talented graduates across many global industries. With this qualification, you’ll be equipped with the skill set and technical knowledge relevant for the data science and big data job market.


Some graduates choose to continue their interest with postgraduate research. The Salford Innovation and Research Centre (SIRC) is home to our world-class research focused on the advancement of informatics, knowledge discovery and semantic web, software engineering, big data, data mining and analytics, cyber security, information visualisation, and virtual environments.

Learn more about postgraduate research opportunities available through our Doctoral School.

A taste of what you could become

A data scientist

A statistician

A data engineer

A data analyst

A machine learning engineer

And more...

Career Links

Salford leads an industrial liaison committee to gain advice on our computing programmes and course content. Companies involved in this initiative include Web Applications UK, AutoTrader, Cooperative, DAI and FastWebMedia - a mixture of companies who rely on IT and data for their operations. This diversity ensures we understand industry needs from multiple perspectives and helps us to nurture graduates with strong employability and transferable skill sets.


What you need to know


This course is ideal for mathematics, computing or science graduates, and experienced professionals, eager to join the data storytelling revolution. 


International applicants are required to demonstrate proficiency in English. An IELTS score of 6.0 (with no element below 5.5) is proof of this.


As part of the course preparation, you will attend an intensive one-week session prior to the start of the course. This session will review basic statistics and database concepts, plus an overview of either Python or R programming for data analysis. 


This degree is partially-accredited by BCS, the Chartered Institute for IT. A partially accredited degree provides a valuable contribution towards professional membership and evidencing breadth of knowledge. Some employers give preference to applicants who have accredited degrees, and an accredited degree is likely to be recognised by other countries that are signatories to international accords.

Standard entry requirements

Undergraduate degree

The minimum requirement is a second class division honours degree or equivalent in any discipline, with previous demonstrable mathematical aptitude e.g. (A-level or BTEC Mathematics).

Alternative entry requirements

Accreditation of Prior Learning (APL)

We welcome applications from students who may not have formal/traditional entry criteria but who have relevant experience or the ability to pursue the course successfully.

The Accreditation of Prior Learning (APL) process could help you to make your work and life experience count. The APL process can be used for entry onto courses or to give you exemptions from parts of your course.

Two forms of APL may be used for entry: the Accreditation of Prior Certificated Learning (APCL) or the Accreditation of Prior Experiential Learning (APEL).

How much?

Type of study Year Fees
Full-time home 2021/22 £8,640per year
Full-time international 2021/22 £15,030per year
Part-time 2021/22 £1,440 per 30 credits
Additional costs

Having your own laptop (16GB of RAM and an Ethernet port) is not essential, but it will give you more flexibility in where and how you engage with the software you will need to use during your studies (software is provided as part of the course).

You should consider further costs which may include books, stationery, printing, binding and general subsistence on trips and visits.

Scholarships for international students

If you are a high-achieving international student, you may be eligible for one of our scholarships.
We have a range of scholarships available for students applying for courses in 2020-2021 and 2021-2022. Our Global Gold Excellence Scholarship is worth £3,500 and our Global Silver Excellence Scholarship is worth £3,000 - both are available for students studying in our 2021/22 intakes.

We also offer the Salford International Excellence Scholarship which offers up to £5,000 discount on tuition fees. As this is a prestigious award we have a limited number of these scholarships available.

See the full range of our International Scholarships.

Apply now

All set? Let's apply

Enrolment dates

September 2021

January 2022

September 2022