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Key details

Start date(s)
January 2026, September 2026
Study Mode
Full-time (1 year)
Full-time (16 months)
Part-time (2 years)
Location
Leeds City Campus
School
Computing and Creative Industries

Are you interested in understanding your right to know how and where data is used in the digital era? Do you want to contribute to improving decision-making on critical and complex problems?

In today's world, we rely increasingly on technologies such as phones, computers, and IoT devices to shop, bank, travel, communicate, socialise, manage and monitor health conditions. As a result, data is being collected at an unprecedented rate, by every industry and organisation, to inform decisions that benefit their business, society, and the environment. This programme aims to create a new generation of accountable and responsible experts in Data Science and AI, reflecting the needs of employers and the skillset and qualities that define proficiency in these fields. Get ready to empower yourself and make a positive impact in the world of data science and AI.

You can choose from four study routes:

Full-time, 1 year (September start)

Full-time, 16 months (January start, includes a summer break)

Part-time, 2 years (September start)

The Student Contract

About this course

Designed in collaboration with key stakeholders including students, employers, academics and external advisors, this programme aims to enable you to develop skills of logical, explorative, analytical and critical thinking in intelligent decision support systems.

Delivered by expert lecturers and industry experts with evidence of research within the Data Science and AI field, each module covers essential elements of data and intelligence with increasing complexity of the knowledge and skills you will need to understand in the digital era.

Real-world case studies will be used throughout the course, and you’ll also have the opportunity to carry out a professional work placement, putting into practice what you’ll learn in your taught sessions.

On successful completion of the MSc Data Science and Artificial Intelligence, you could work in a number of roles, which could include Data Analyst, Strategic Data Insight, AI Developer, AI Data Engineer, Business Intelligence Analyst, ML Engineer or Data Scientist. This degree will also prepare you for further study, such as pursuing a PhD.

There are various start dates to suit you.  

Why study with us

  • Gain hands-on experience with access to real-world assessment strategies and successfully demonstrate industry-based skills and innovation in decision support and data-driven decision-making.
  • Acquire knowledge of ethical and legal issues that inform data and AI.
  • Develop multi-disciplinary skills in statistics and computing.
  • Put into practice what you learn in taught sessions with professional work placements, working on real-world problems.
  • Receive financial support through a PG loan or bursary. 
  • There are various start dates to suit you. Please refer to the course structure tables below.
Student working on laptop in classroom.

Course modules

You will study a variety of modules across your programme of study. The module details given below are subject to change and are the latest example of the curriculum available on this course of study.

Core modules

You will study the following modules throughout your degree. View the Course Structure tables regarding the different start dates.

Secure Software Development –

You’ll be introduced to programming where you’ll learn the fundamental programming languages and their applications to solve complex problems using secure and technical solutions.

Gain hands-on experience through practical exercises and assignment and develop your problem-solving skills through our problem-based learning approach and gain an understanding on data structures and security related issues of programming as you explore and develop your capabilities in wiring software solutions.

Explore software best practices and secure development principles such as modularity, documentation, version control and collaboration tools.

Artificial Intelligence –

You'll gain the ability to tackle real-world problems in the field of data science and AI.

Focus on practical, problem-solving perspectives and learn the stages of artificial intelligence and machine learning to model intelligent predictive solutions that help enterprises achieve sustainability in their businesses.

You'll have the opportunity to practice a range of algorithms, from fundamental linear regression and decision trees to advanced techniques like neural networks.

Learn how to turn raw data into actionable insights, predict outcomes, and uncover hidden secrets using industry-level tools. You'll also explore some fundamental ideas of deep learning.

Data Science and Visualisation –

You’ll be equipped with the theoretical and practical knowledge of data analytics and data visualisation required to solve computational challenges related to the use of data and to add business value.

Gain the essential theoretical and practical skills needed to understand database design, data mining, analytics, and visualisation using appropriate tools.

Explore topics from a range of application areas such as sustainability, manufacturing, and the economy.

You’ll work with real data to explore and solve known problems by analysing different types of datasets. You’ll also take a practical approach to learning, with topics explored through the study of applied examples.

Responsible Computing –

Develop an in-depth understanding of the ethical and social implications of computing. You’ll be equipped with the knowledge, skills and tools you’ll need to identify and address ethical challenges that arise in the design, development and use of computer systems.

You’ll cover areas such as responsible conduct of research, intellectual property, privacy, security and accessibility and explore case studies and engage in group discussions to analyse real-world ethical dilemmas.

You’ll understand how to design and implement systems that are accountable to their users and stakeholders and how to ensure transparency in the decision-making processes.

Project –

Engage with the research and production of a substantial report based on investigating a problem and developing a solution in the form of an artefact.

Your project will be relevant to your programme and is the culmination of your studies, drawing heavily on the material and skills you've developed throughout your studies.

You’ll have the opportunity to showcase your comprehensive understanding and critical evaluation of specialised academic knowledge, the application of innovative research techniques, and the ability to independently address complex issues and communicate findings while considering ethics and integrity. You will focus on self direction and originality in addressing and resolving problems, along with the ability to work autonomously while planning and executing tasks at a professional or comparable level.

Course structures

Please see the course structure tables for the different start dates below. 

If you choose to study the MSc Data Science with Artificial Intelligence with Professional Placement, your first year will follow either the full-time one-year September or January start course structure tables below.

Your Professional Work Placement in industry or through a placement based at the University is equivalent to and replicates an authentic professional or research environment. You will carry out the Professional Placement across all three terms and will be worth 120 credits. 

September - Full-time, 1 year programme
Year Term Module Credits Contact Hours
1 1 Secure Software Development 30 10 x 3 hours
Data Science and Visualisation 30 10 x 3 hours
2 Responsible Computing 30 10 x 3 hours
Artificial Intelligence 30 10 x 3 hours
3 and Summer Project 60 4 x 3 hours workshops plus 6 x 30-minute supervision meetings
September - Part-time, 2 year programme
Year Term Module Credits Contact Hours
1 1 Secure Software Development 30 10 x 3 hours
2 Responsible Computing 30 10 x 3 hours
2 1 Data Science and Visualisation 30 10 x 3 hours
2 Artificial Intelligence 30 10 x 3 hours
3 and summer Project 60 4 x 3 hours plus 30-minute supervision meetings
January - Full-time, 16 month programme
Year Term Module Credits Contact hours
1 1 (Jan - Mar) Responsible Computing 30 10 x 3 hours
Artificial Intelligence 30 10 x 3 hours
2 (Apr - May) Project module preparation and initial project proposal development
May - Sept Summer break
2 (Sept - Dec) Secure Software Development 30 10 x 3 hours
Data Science and Visualisation 30 10 x 3 hours
2 3 (Jan - May) Project 60 4 x 3 hour workshops plus 6 x 30-minute supervision meetings

Got a question about the course?

Our Computer Science team are on hand to answer your questions, whether you want to know about the modules you'll be studying, where you can complete your professional placement or the types of assessments you'll do, they are here to help.

Learning and teaching

Assessments are based on practical scenarios where you will apply your knowledge of the topics covered to solve defined problems. You will be assessed through a variety of methods, including:

  • Reports
  • Presentations
  • Portfolios
  • Software artefacts

Programme delivery

Your time on campus, learning through in-person teaching, is at the heart of your academic experience and the way we deliver our programmes. This is supported and further enhanced by additional engagement activities and opportunities provided online and through digital teaching materials. This blended approach seeks to ensure a positive learning and teaching student experience.

Your programme of study has been carefully designed around a three-phase model of delivery:

  1. Preparation: You will be given clear tasks to support you in preparing for live teaching. This could include watching a short-pre-recorded lecture, reading a paper or text chapter or preparing other material for use in class.
  2. Live: All your live teaching will be designed around active learning, providing you with valuable opportunities to build on preparation tasks, interact with staff and peers, and surface any misunderstandings.
  3. Post: Follow-up activities will include opportunities for you to check understanding, for staff to receive feedback from you and your peers to inform subsequent sessions, and for you to apply learning to new situations or context.

Preparation, Live and Post teaching and learning and the digital materials used will vary by course, but will be designed to help you structure your learning, take a full and active part in your course, and apply and test your developing knowledge and skills.

Learning and teaching

At Leeds Trinity we aim to provide an excellent student experience and provide you with the tools and support to help you achieve your academic, personal and professional potential.

Our Learning, Teaching and Assessment Strategy delivers excellence by providing the framework for:

  • high quality teaching
  • an engaging and inclusive approach to learning, assessment and achievement
  • a clear structure through which you progress in your academic studies, your personal development and towards professional-level employment or further study.

We have a strong reputation for developing student employability, supporting your development towards graduate employment, with relevant skills embedded throughout your programme of study.

We endeavour to develop curiosity, confidence, courage, ambition and aspiration in all students through the key themes in our Learning and Teaching Strategy:

  • Student Involvement and Engagement
  • Inclusion
  • Integrated Programme and Assessment Experience
  • Digital Literacy and Skills
  • Employability and Enterprise

To help you achieve your potential we emphasise learning as a collaborative process, with a range of student-led and real-world activities. This approach ensures that you fully engage in shaping your own learning, developing your critical thinking and reflective skills so that you can identify your own strengths and weaknesses, and use the extensive learning support system we offer to shape your own development.

We believe the secret to great learning and teaching is simple: it is about creating an inclusive learning experience that allows all students to thrive through:

  • Personalised support
  • Expert lecturers
  • Strong connections with employers
  • An international outlook
  • Understanding how to use tools and technology to support learning and development

Entry requirements

Leeds Trinity University is committed to recruiting students with talent and potential and who we feel will benefit greatly from their academic and non-academic experiences here. We treat every application on its own merits; we value highly the experience you illustrate in your personal statement.

The following information is designed to give you a general overview of the qualifications we accept. If you are taking qualifications that are not included below, please contact our Admissions Office who will be happy to advise you.

Our MSc programme is open to individuals from all backgrounds, not just computer science graduates. We believe in the power of diverse perspectives and are dedicated to supporting you in pivoting your expertise.

Whether you hold an honours degree (minimum 2.2) in a computing-related subject or have equivalent professional experience in the field, or even if your degree is non-STEM, you are welcome to apply to us.

We understand that academic qualifications do not define your potential, and we provide opportunities to ensure that everyone, regardless of their background, has the opportunity to apply to study the MSc degree with us.

For more information on meeting English language requirements and academic requirements by country, visit our International Applicants page.

Please contact us for personalised advice on 0113 283 7123 or at admissions@leedstrinity.ac.uk

Fees and finance

Funding

UK Home Students:

For information about our tuition fees please visit our Student Fees and Finance pages.

If you studied your undergraduate degree at Leeds Trinity University, you may be eligible for a discount of up to 50% on the cost of your tuition fees.

International Students, including EU Students:

Visit our web page for international students.

Leeds Trinity Alumni Discount

Some Leeds Trinity graduates are eligible for a tuition fee discount on postgraduate courses of up to 50%, excluding PGCE Delivery Partner Model and Lead Partner Model, and Masters by Research courses. You will need to achieve a 2:2 or above in a Leeds Trinity undergraduate course to qualify.

Postgraduate course Leeds Trinity Alumni Discount
MSc programmes  50% for Leeds Trinity graduates with a 1st class honours degree
MSc programmes 35% for Leeds Trinity graduates with a 2:1 honours degree
MSc programmes  20% for Leeds Trinity graduates with a 2:2 honours degree

 

How to apply

Applications for January 2026 starts are now closed - applications for a September 2026 are open.

Please ensure you complete the application form in full and supply all the required supporting documentation when you make your initial application. Incomplete applications may be rejected.

If you need advice on your application, please contact our admissions team on 0113 283 7123 (Monday to Thursday, 9.00am to 5.00pm, or Friday 9.00am to 4.00pm) or admissions@leedstrinity.ac.uk

Home applicants - How to apply

Applicants who require a Student Route Visa

Student Route Visa applications to study in January 2026 are now closed.

Applicants who require a Student Route Visa in order to study in the UK for a September 2026 start - deadline for applications is Monday 1st June 2026.

Part-time study is not available for international students on a Student Route Visa.

For additional information, including academic requirements by country, visit our .

What happens next?

Our admissions team will acknowledge receipt of your application by email.

Where applications are submitted but references are still in progress, admissions will wait for the reference(s) to be received and then will process it, and forward it to the relevant Programme Leader within five days of receipt of the reference(s).

The Programme Leader will make a decision based on your application. You may be asked to provide a reference to demonstrate your academic and non-academic experiences, or you may be invited to attend an interview. If you are successful and are made an offer, the conditions will be outlined in your offer letter.

Applications will be acknowledged within five working days. Applicants will be contacted within 15 working days with a request for additional information, an invitation to an informal interview or an application decision.

Made an offer?

You should accept or decline your offer by emailing admissions@leedstrinity.ac.uk.

If you accept, you'll need to prove you satisfy the conditions outlined in your offer letter.

You may be asked to present the relevant supporting documentation in person to the student information point on campus - if originals are not needed, you’ll be contacted and given details of how to provide the supporting documentation.