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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 five study routes:
Full-time, 1 year (September start)
Full-time, 16 months (January start, includes a summer break)
Full-time, 2 years with Professional Placement (September start)
Full-time, 28 months with Professional Placement (January start, includes a summer break)
Part-time, 2 years (September start)
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.
The full-time Professional Placement option offers you the chance to enhance your qualification by spending a year completing an industry placement or engaging with a research project at the University. Although we cannot guarantee placements for students, we will provide you with practical support and advice on how to find and secure your placement.
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.
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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.
You will study the following modules throughout your degree. View the Course Structure tables regarding the different start dates.
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.
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.
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.
Develop and in-depth understanding of the ethical and social implications of computer. 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.
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.
You may choose to study this course with a Professional Placement.
This module allows you to develop, practice and demonstrate skills relevant to your programme of study in a professional work environment.
You must select one of the following two options for your Professional Placement.
Industry Placement
Spend a year working full-time in industry. You will have an opportunity to apply to a range of advertised placements, which will offer you the chance to develop your knowledge and professional skills in a professional workplace setting. Although we cannot guarantee placements for students, we will provide you with practical support and advice on how to find and secure your placement.
Research Project
Develop your research and academic skills by working as a member of a research team being led by one of our leading researchers. Experience working as part of a research team in an academic setting. Ideal for those who are interested in a career in academic or industrial research or consultancy.
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.
| 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 |
| Year | Term | Module | Credits | Contact Hours |
|---|---|---|---|---|
| 1 | 1 | Secure Software Development | 30 | 4 x 3 hours |
| Data Science and Visualisation | 30 | 4 x 3 hours | ||
| 2 | Artificial Intelligence | 30 | 4 x 3 hours | |
| Responsible Computing | 30 | 4 x 3 hours | ||
| 3 and Summer | Project | 60 | 4 x 3 hour workshops plus 30-minute supervision meetings | |
| 2 | 1, 2 and 3 | Professional Placement | 120 | TBC |
| 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 |
| 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 |
| 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 |
| 2 and 3 | 1, 2 and 3 (May - May) | Professional Placement | 120 | TBC |
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.
Assessments are centred around a real-world scenario where you will need to apply your knowledge of the topics covered to solve given problems. You will be assessed by various methods, which include:
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:
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:
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:
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 [email protected]
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.
Visit our web page for international students.
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 |
There is no official closing date for applications, but the course will be closed when it is full. We therefore encourage you to make your application as early as possible.
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 [email protected]
Home applicants - How to apply
Applications for January 2025 are now closed for students who require a Student Route Visa in order to study in the UK.
For a September 2025 start, if you require a Student Route Visa in order to study in the UK, then you must apply to us by Friday 18 July 2025.
Part-time study is not available for international students on a Student Route Visa.
For additional information, including academic requirements by country, visit our country and region page.
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 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 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, invite to an informal interview or an application decision.
You should accept or decline your offer by emailing [email protected].
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.