Artificial Intelligence and Machine Learning MSc

Attendance mode

Entry year

Duration: 1 year; 1 year
Start date: September; September
Location: City Campus; City Campus

Suitable for UK and internationalUK and international applications.

Overview

Artificial Intelligence (AI) and Machine Learning (ML) is an exciting, cutting-edge topic with technologies and applications that span almost every aspect of our lives. AI and ML are everywhere, from smartphone apps that recognise your speech, to self-driving cars that revolutionise the safety and efficiency of our transport networks.

AI and ML are built on a foundation of computer science. It combines problem-solving skills, practical skills like programming, and specialist knowledge on tools and techniques for creating smart algorithms and software.

On this course, you will benefit from our 50 years-plus of experience in computer science. You'll learn how to integrate a diverse set of skills from a variety of topics into real-world applications, through our industry-focused curriculum.

You will study topics such as programming, machine learning, classification, clustering, AI in Healthcare and more, with modules that challenge you to combine and apply these topics on practical projects with career-launching outcomes.

The programme includes project and dissertation modules with opportunities to leverage industry-standard software tools to develop cutting-edge solutions to real-world problems, with the support and guidance of academic experts from the artificial intelligence domain.

All of our computer science students are automatically enrolled as student members of the British Computer Society (BCS).

Entry requirements

2:2 or above in computer science, computer engineering, informatics or other computer-related subjects (including engineering and management disciplines such as finance, economics, business studies etc) from an approved degree-awarding body.

Candidates who do not fulfil the normal entry requirements but have extensive industrial experience in a related area are considered on an individual basis.

English language requirements: Minimum IELTS 6.0 or equivalent.

English language requirements: Minimum IELTS 6.0 or equivalent.

Your learning journey

All module information is for 2026/7 entry and is subject to change.

First year

Core

MSc Group Project

Conducting projects is an integral part of academic and/or professional career. Some projects fail due technical reasons, but most failures are directly related to the poor project management and not applying the principles of good project management. In this module, the students will learn project management processes that project teams must understand and the standards to which their projects are being held to and apply these principles in a practical project. The module gives students experience of carrying out a computer science research project that solves a particular research problem relevant to the programme of study (e.g. Artificial Intelligence, Big Data Systems, Internet of Things, etc.). The students will either provide a computational solution using scientific tools and methods and performing computational analysis, or they provide a software engineering solution by developing a fully functional software system using state-of-the-art software development techniques. The students will also analyse legal, social, ethical and professional issues related to their projects. By working in teams, the students are expected to demonstrate the need for a professional approach to all aspects of research and software development. As part of the project, teams will deliver reports, code, and demonstrate a working software system or a computational solution. In addition, they will present certain elements of their work in written, graphical and verbal forms through the production of materials, e.g., reports, demo, and oral presentation. The students will be guided by a supervisor from the relevant research disciplines.

Advanced Machine Learning

The application of Artificial Intelligence to real world problems particularly facing big data challenges often requires the use of complex machine learning algorithms chosen from a broad and deep range of possible knowledge and tools. Understanding the context within which predictive modelling, data clustering and other techniques operate, and how to appropriately select and use them for a defined purpose, requires an understanding of both theoretical concepts and practical aspects of Computer Science and Artificial Intelligence.

Artificial intelligence is part of everyday life across the world, providing cutting edge digital technology solutions, opportunities and challenges in every economic, scientific, social, health and environment sector amongst others, including business, education, care, manufacturing, finances, travel, biodiversity and wellbeing, while supporting also scientific discoveries and progress.

In this module, you will have the opportunity to grow and apply the knowledge and skills assimilated and imparted during all years of your programme of studies and advance your problem-solving skills through the solution of a problem normally involving research, analysis, design and practical development of a machine learning product or process.

The module aims to explore and define current theoretical knowledge including data, information, knowledge and intelligence concepts, also explore in depth understanding of analysis, algorithms and techniques used to enable sustainable machine learning technologies and models, and to develop practical skills in applying them in specific contexts. Consequently students will have the necessary domain knowledge and applied skills to understand the problem, define project requirements and select/use a range of appropriate techniques and processes to produce a suitable solution.

For our Computer Science programmes the British Computer Society (BCS - The Chartered Institute for IT) - is the key Professional, Statutory, and Regulatory Body (PSRB). The accredited programs ensure meeting the standards required for graduates to enter the profession and gain recognition as IT professionals. The accreditation, that involves a rigorous review process, including curriculum evaluation, teaching quality, and the relevance of the program to industry needs and professional career building, is relevantly addressed by the enclosed module Learning Outcomes, Teaching and Learning Methods, Assessment Strategy and delivery.

Advanced Topics in AI and Digital Healthcare

The use of advanced AI techniques for real world situations requires advanced knowledge of both the tools and techniques themselves as well as the context within which they operate; ethically, legally, and societally. This module aims to provide students with knowledge advanced theories, concepts, techniques in Artificial Intelligence, Machine Learning and Data Mining applied to real world data as well as the regulatory and societal context surrounding them. Students will explore how tools and algorithms can be used in applied areas such as Digital Healthcare, Blockchain and a variety of other fields in terms of developing practical solutions that incorporate wider, non-technical issues.

The module will combine theoretical knowledge with hands on skills through selected software tools, platforms and online solutions.

Dissertation

The Dissertation for all MSc programmes is driven by the student's aspirations and preferences and draws on and enhances the professional skills and knowledge gained by the student during the taught component of the course. The student must select relevant tools and techniques acquired throughout their specific program of study (AI, Cyber Security, or Big Data) and design and develop a solution to a practical problem or challenge by using either (1) a real-world data set or (2) a generated hypothetical data set. Completing their dissertation, the student will be able to demonstrate evidence of achieving the program learning outcomes and graduate attributes and be able to o demonstrate these to future employers, including consideration of legal, social, ethical, and professional issues relevant to their topic.

Software Development

Software solutions enable computers to function efficiently and accurately in tasks such as automating processes, collecting data, analysing information and decision making on real-world issues relating to such as social justice, climate change, spread and control of epidemics, prediction of natural disasters, etc. This module offers an ideal introduction to programming knowledge and skills required for developing software solutions for data science, Artificial Intelligence (AI) and related areas.

Cloud AI

Are you excited to use massive amounts of data to develop Artificial Intelligence (AI) models on the cloud? Eager to learn from many different enterprise's use cases of cloud AI? Want to help the largest global enterprises derive business value through the adoption of AI?

In this module, you will learn the basics of cloud computing, including the advantages and disadvantages of cloud computing. We will reveal what cloud services such as Amazon Web Services are and the Cloud Adoption Frameworks. This course assumes you have a non-IT background, as it will not teach you how to build applications in the cloud. This course will give you a general conceptual understanding of cloud AI frameworks and services.

Optional

Responsible AI: Ethics, Law and Governance

The module aims to explore and judge the nature and scope of AI interventions, the legal, social, moral and ethical implications of these technologies and their impact on societies and government institutions.

With the ever increasing adoption of AI systems for decision making, customer service, modelling and many other applications, the impact these systems have on our everyday lives must be examined and critically assessed in terms of their fairness, their compliance with legal frameworks and how they affect the diverse populations around the world.

Big Data Visualisation (PG)

The aim of this module to provide you with key principles and techniques of data visualisation.

By completing this module you will gain advanced knowledge and skills on developing methods and techniques of data visualisation to improve comprehension, communication, and decision making in big data applications.

All module information is for 2026/7 entry and is subject to change.

First year

Core

MSc Group Project

Advanced Machine Learning

Advanced Topics in AI and Digital Healthcare

The module will combine theoretical knowledge with hands on skills through selected software tools, platforms and online solutions.

Dissertation

Software Development

Cloud AI

Optional

Responsible AI: Ethics, Law and Governance

Big Data Visualisation (PG)

The aim of this module to provide you with key principles and techniques of data visualisation.

Teaching, learning and assessment

Learning and teaching activities include lectures that introduce and explore theory, concepts, and case studies that illustrate how practical outcomes are derived from theoretical principles. In laboratory sessions, you will use industry-standard tools hands-on to develop practical skills relevant to your subject. These sessions also facilitate individual and small group feedback. Seminars and tutorials help to build communication, teamwork and strengthen the connections between theory and practice.

Most modules in this course will assess your attainment through practical coursework exercises, reflecting the emphasis on demonstrable applied skills that support future career paths and progression. Assessments using real world problems and limited scope case studies will increase your engagement, creating stronger links between the academic subject, the assessment of learning outcomes, and transferrable skills. Written or computer-based examinations are also used to measure specific theoretical and knowledge aims, which are also assessed in written reports for many coursework assignments.

Teaching, learning and assessment

Fees, finance and scholarships

Tuition fee

Home: £9,940
International: £15,700

Tuition fee

Home: £10,189
International: £16,092

Additional course costs

While there are no compulsory additional costs associated with this course, there may be general additional costs that you may incur as a student. A list of the sort of costs you might expect can be found on our fees and finance section.

Funding your studies

It can be hard to know what financial help is available to you as a student.

Further information about the variety of options that can help fund your studies and maximise the money available to you is available on our funding your studies section.

Scholarships

Every year we award numerous non-repayable scholarships to UK, EU and international students on the basis of academic excellence, personal circumstances or economic hardship. For full details, visit our scholarships section.

Career opportunities

The University is committed to helping students develop and enhance employability and this is an integral part of many programmes. Specialist support is available throughout the course from Career and Employability Services including help to find part-time work while studying, placements, vacation work and graduate vacancies. Students are encouraged to access this support at an early stage and to use the extensive resources on the careers section.

Support for your studies

At Bradford, we’re committed to supporting your success, well-being and future ambitions. We’re here to provide everything you need to make the most of your time with us, ensuring you not only excel in your studies, but also step confidently into the world of graduate employment. In addition to the support you receive from your academic tutors, our Student Support Services are here for you throughout your journey - before, during, and after your studies.

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Terms and conditions of study

The University has a set of terms and conditions for all students accepting an offer to study on a course here at Bradford. This is called The Student Contract. This document sets out the Terms and Conditions which apply when you accept an offer of a place on a programme of study at the University of Bradford.

View our Student Contract for further details.

Transparency statement

Information about this programme and its modules has been published in advance of the academic year to which it applies. Every effort has been made to ensure that the information is accurate at the time of publication, but changes may occur given the interval between publishing and commencement of teaching. Any change which impacts the terms and conditions of an applicant’s offer will be communicated to them.