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Postgraduate study
Computing & Cyber Security

Applied Data Science MSc

Data scientists are responsible for the handling of raw data, analysing it, identifying patterns and presenting insights in a manner that is useful for forecasting and predicting business problems. The data science field uses mathematics, statistics, machine learning, a range of computer science disciplines and a common toolset such as Python, SQL, and R.


Course overview

MSc Applied Data Science

See what it’s like to study MSc Applied Data Science and if you’re eligible for a £10k scholarship

Data scientists are in high demand as government departments and leading companies realise the importance of big data and its applications to developing successful strategies in their decision making or business relations.

You gain technical and critical thinking skills in applying knowledge of data science to real-world problems, and learn fundamentals of software for digital innovation, applied machine learning, big data and business intelligence, interactive visualisation of data, and applications. You explore professional, ethical, security and social implications of future data science technologies, and gain a range of transferable skills to progress into industry.

Progressing from almost any first degree discipline, you gain leading-edge skills, solid programming experience, research expertise and optional industry experience to enter this field and rapidly expanding job market. You work closely with our AI and Machine Learning research groups, and have the opportunity to undertake an internship. You can choose from three routes:

  • One year full-time – a great option to gain a traditional MSc qualification.
  • Two years full-time (including Advanced Practice) – enhances the qualification by adding a vocational or research-based internship to the one-year programme. This is a great way to gain work experience and give your CV a competitive edge. A research internship provides the opportunity to develop analytical, team-working, research and academic skills by working alongside a research team in an academic setting. We guarantee a research internship, but cannot guarantee a vocational internship. We provide practical support and advice on how to find and secure vocational internship positions.
You may be eligible for a £10,000 Artificial Intelligence and Data Science Office for Students Scholarship to support your studies.

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Course details

Course structure

Core modules

Artificial Intelligence Ethics and Applications

You gain a deep insight into the business applications of artificial intelligence (AI) and data science (DA). You explore a range of AI and DS applications such as chatbots, virtual assistants, medical diagnosis, biometric recognition, personalisation, fraud detection and autonomous machines, and analyse both the risks and opportunities of applying AI and DS techniques in these areas.

Big Data and Business Intelligence

You develop your ability to design and implement database, big data and analytics applications to meet business needs. A case study is used to follow the system development lifecycle. You develop a plausible application from inception to implementation for a real-world scenario.

You investigate the issues and technologies associated with implementing and supporting large scale databases and the services that are needed to maintain and access a repository of data. Investigations are undertaken in a number of areas including big data, data warehouses, integrating legacy data, data management and approaches that support the modelling and visualisation of data for a range of use views.

Computing Masters Project

You undertake a major, in-depth, individual study in an aspect of your course. Normally computing master’s projects are drawn from commercial, industrial or research-based problem areas. The project involves you in researching and investigating aspects of your area of study and then producing a major deliverable, for example software package or tool, design, web-site and research findings. You also critically evaluate your major deliverable, including obtaining third party evaluation where appropriate.

The major deliverable(s) are presented via a poster display, and also via a product demonstration or a conference-type presentation of the research and findings. The research, project process and evaluation is reported via a paper in the style of a specified academic conference or journal paper. The written report, the major deliverable and your presentation of the product are assessed.

The project management process affords supported opportunities for goal setting, reflection and critical evaluation of achievement.

Data Science Foundations

Gain an introduction to core data science concepts and tools, focusing on real-life data science problems with practical exposure to relevant software. Topics such as preparing and working with data, data visualisation and databases are covered.

Interactive Visualisation

Dynamic, interactive visualisations enable the reader to explore the data for themselves through a variety of perspectives. Static visualisations are excellent for print medium but are restricted to showing a single perspective and do not handle multidimensional datasets well. Using an interactive graphic the reader can zoom in on sections of the data which are of interest, explore more than one dimension at a time, and sort and filter to discover new patterns and themes within the data. Particularly useful is the ability to provide a macro/micro view of the same data, ie a big picture view of the full dataset from which the reader can then ‘drill down’ into the lower level detail.

This module uses the javascript library for Data-Driven Documents (D3js) for creating animated, dynamic graphics for the web, and looks at other alternatives available.

Machine Learning

Machine learning is a subfield of computer science concerned with computational techniques rather than performing explicit programmed instructions. You build a model from a task based on observations in order to make predictions about unseen data. Such techniques are useful when the desired output is known but an algorithm is unknown, or when a system needs to adapt to unforeseen circumstances.

You explore statistics and probability theory as the fundamental task is to make inferences from data samples. The contribution from other areas of computer science is also essential for efficient task representation, learning algorithms, and inferences procedures. You gain exposure to a breadth of tasks and techniques in machine learning.

Assessment is an in course assessment (100%).

Software for Digital Innovation

You gain an introduction to the Python programming language and its application to solving problems in digital innovation. This involves the principles of programming, the syntax and structure of Python, its relevant libraries and modules, and how it is incorporated in existing software tools. You form a solid foundation of producing software solutions to real-world problems.


Advanced practice (2 year full-time MSc only)


The internship options are:

Vocational: spend one semester working full-time in industry or on placement in the University. We have close links with a range of national and international companies who could offer you the chance to develop your knowledge and professional skills in the workplace through an internship. Although we cannot guarantee internships, we will provide you with practical support and advice on how to find and secure your own internship position. A vocational internship is a great way to gain work experience and give your CV a competitive edge.

Research: develop your research and academic skills by undertaking a research internship within the University. Experience working as part of a research team in an academic setting. Ideal for those who are interested in a career in research or academia.


Modules offered may vary.


How you learn

You learn concepts and methods through lectures, labs and tutorials using case studies and examples. Lectures include presentations from industry guest speakers. Critical reflection is key to successful problem solving and essential to the creative process. You develop reflective practice at an advanced level, then test and assess solutions against criteria through research.

Expect blended delivery of learning material, with a mix of face-to-face and online learning.

How you are assessed

You are assessed on your subject-specific knowledge, cognitive and intellectual skills and transferable skills applicable to the workplace. The assessments include assignments, tests, case studies, presentations, research proposal and literature review, and a dissertation. The assessments may include individual or group essays or reports. The assessment criteria, where appropriate, includes assessment of presentation skills and report writing.


Entry requirements

Normally a first degree (2.2 minimum), relevant experience or equivalent qualifications. Any first degree subject* is considered excluding BSc (Hons) Computer Science, BSc (Hons) Artificial Intelligence and BSc (Hons) Data Science.

Entry from some first degree disciplines including BSc (Hons) Computing and BSc (Hons) Information Technology depends on course content. You are required to provide a full transcript of studies to enable our admissions team to determine your eligibility.

In addition, international students will require IELTS 6.0 or equivalent.

For general information please see our overview of entry requirements

International applicants can find out what qualifications they need by visiting Your Country



Career opportunities

The increasing need to leverage big data has motivated many industries to hire data scientists to predict the outcomes and provide meaningful interpretations. Companies hiring data science professionals include American Express, AstraZeneca, BBC, IBM, Mastercard, Rolls Royce, Space Ape Games, Warner Bros. Entertainment, WhatsApp, plus many more.

Graduates can expect to find employment in one of the increasing number of sectors needing specialists equipped with the cutting-edge expertise in financial and digital technologies.

According to, the median salary in the UK for data science professionals is £65k but the top 10% can earn upwards of £100k.

We prepare you for a career in industry. In addition to your taught classes, we create opportunities for you to meet and network with our industry partners through events such as our ExpoSeries, which showcases student work to industry. ExpoTees is the pinnacle of the ExpoSeries with over 100 businesses from across the UK coming to the campus to meet our exceptional students, with a view to recruitment.

Work placement

Students on the two-year full-time route complete a 60 credit Advanced Practice module.


Information for international applicants


International applicants - find out what qualifications you need by selecting your country below.

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Useful information

Visit our international pages for useful information for non-UK students and applicants.

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2024/25 entry

Fee for UK applicants
£7,365 a year

£4,770 a year with Advanced Practice

More details about our fees

Fee for international applicants
£17,000 a year

£10,000 a year with advanced practice

More details about our fees for international applicants

  • Length: 1 year or 2 years with Advanced Practice
  • Start date: September
  • Semester dates

Apply now (full-time)



2024/25 entry

Fee for UK applicants
£820 for each 20 credits

More details about our fees

  • Length: Up to 3 years
  • Attendance: Tuesday and Thursday 6.00pm - 9.00pm
  • Start date: September
  • Semester dates

Apply now (part-time)

Apply now (part-time)


Choose Teesside

  • Student and graduate profiles

    Janine Arif

    Janine ArifMSc Applied Data Science

    Teesside University offer a wide range of courses and the staff are excellent

    Meet Janine

    Mohana Kamanooru

    Mohana KamanooruMSc Applied Data Science

    This course has also not only increased my knowledge but has also made me more enthusiastic about the field.

    Meet Mohana


Get in touch

UK students


Telephone: 01642 738801

Online chat (general enquiries)

International students


Telephone: +44 (0) 1642 738900

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