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Postgraduate study
Computing & Cyber Security

Applied Artificial Intelligence MSc

Artificial intelligence (AI) enables a digital computer or computer-controlled robot to learn, reason, discover meaning and perform tasks commonly associated with intelligent beings. AI applications include gaming, medical diagnosis, computer search engines, and voice or handwriting recognition.


Course overview

MSc Applied Artificial Intelligence

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

You gain technical and critical thinking skills in applying knowledge of AI to real-world problems, and learn fundamentals of software for digital innovation, applied machine learning, big data and business intelligence, deep learning and applications. You explore professional, ethical, security and social implications of future AI 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.

Artificial Intelligence Foundations

You gain the foundational knowledge to study a wide range of AI applications and solutions, and are introduced to logic-based knowledge representation, reasoning, problem solving and algorithms, planning and AI applications.

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.

Deep Learning

Deep learning is a subset of machine learning that uses artificial neural networks models with many layers to solve problems in computer vision, speech recognition, natural language process and language translation. The main advantage of deep learning is the ability to learn representations from raw data such as images or text without the need to hand engineer features that represent the input for the model and deliver very high accuracy. Deep learning is now the main technology behind many breakthroughs in object and voice recognition, Google Deep Mind AlphaGo, Siri (Apple), Alexa (Amazon) and Face recognition (Facebook). This module covers various deep learning methods and their practical applications.

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 excluding BSc (Hons) Artificial Intelligence, BSc (Hons) Computer Science, 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

Examples of specific jobs held by AI professionals include:

• software analysts and developers
• computer scientists and computer engineers
• algorithm specialists
• research scientists and engineering consultants
• mechanical engineers and maintenance technicians
• manufacturing and electrical engineers
• surgical technicians working with robotic tools
• medical health professionals working with artificial limbs, prosthetics, hearing aids and vision restoration devices.

Companies hiring AI professionals include Amazon, Google, Microsoft, Facebook, Huawei, Adobe, Oculus VR, GE and BAE Systems. According to, the median salary in the UK for AI 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
    Lauren McGinney

    Lauren McGinney

    MSc Applied Artificial Intelligence

    I've discovered many new aspects of AI that I’d love to explore in the future – from media to cybersecurity. Coding and AI are valuable skills for so many jobs.

    Meet Lauren


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UK students


Telephone: 01642 738801

Online chat (general enquiries)

International students


Telephone: +44 (0) 1642 738900

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