What you'll learn

This course comprises of the following core modules:

• Fundamentals of Artificial Intelligence Research, Development, and ManagementLink opens in a new window (30 credits)
• Programming for Artificial IntelligenceLink opens in a new window (15 credits)
• Fundamentals of Artificial Intelligence and Data MiningLink opens in a new window (15 credits)
• Artificial Intelligence and Deep LearningLink opens in a new window (15 credits)
• Applied Statistics for Artificial IntelligenceLink opens in a new window (15 credits)
• Ethical Artificial Intelligence ImplementationLink opens in a new window (15 credits)
• Artificial Intelligence for IndustryLink opens in a new window (15 credits)
• MSc Project (60 credits)

Please note that whilst the module catalogue shows the latest approved version of each module and what is currently being taught (academic year 2024), there may be minor updates to content or learning objectives year on year, to reflect the evolving state of knowledge and the requirements of teaching best practise. Any such amends will be updated following the department 'module approvals process' and reflected in the module catalogue before the start of the next academic year in 2025.

Project

In addition to your modules, in order to gain a Master of Science qualification, you will need to undertake a dissertation project, worth 33% of your MSc credits and your final grade (60 credits). This will be a major individual project, which will develop your academic, research, and analytical skills. Your project will enable you to focus on a particular aspect of Artificial Intelligence in order to further your personal and career interests. It will be submitted in the form of a dissertation at the end of the academic year.

You are expected to devote an appropriate portion of your time and intellectual effort to the project during the course i.e. approximately 600 hours over the course of the academic year.

Learning style and assessment

This course has two components – a taught component accounting for two-thirds of your time and effort, and a research component (dissertation) accounting for one-third.

For the taught component, we blend lectures with seminars, syndicate exercises, simulations, and case studies. The majority of modules are taught in small classes to facilitate and encourage interaction. Others practice larger-scale lectures, which are then supported by small class seminars and group activities. Our module leaders have extensive academic and industry experience; guest speakers currently working at the forefront of their fields also contribute regularly to the content and delivery of the course, bringing real-world insight into your learning experience.

Typical contact hours

Module delivery patterns vary, but most will be delivered in a short learning block of up to 4 weeks, allowing your focus to be on one module at a time. Each module nominally accounts for 150 hours, which includes scheduled classroom time and online sessions as well as your independent study and assessments.

As a Master's student, you are expected to manage your own time appropriately. On average, you are expected to commit 38-40 hours of study each week, in order to successfully achieve your Master’s degree.

The 30-credit module: ‘Fundamentals of Artificial Intelligence Research, Development, and Management’ spans 7 weeks and includes 10 hours of lectures, 20 hours of seminars, and 15 hours of project supervision. Additionally, students will engage in 135 hours of self-directed study under the guidance of their project supervisor to complete their project plan during this module.

Assessment

The course uses a variety of assessment methods across modules. These may include reports (both topic-based and reflective), individual and group presentations, skills-based assessments in data analysis, programming, implementation of AI and machine learning algorithms to solve challenges, poster presentations, and critical reflections.

Assessments have been designed not only to assess your achievement in meeting the course learning outcomes in an academically sound manner, but also contribute to preparing you with the requisite competencies required for employment.

Read more information about the course structure.

Entry requirements

In order to meet our academic entry requirement, you should have obtained the minimum of a UK 2:1 undergraduate degree (or equivalentLink opens in a new window) in a relevant technical subject. The course is suitable for STEM graduates, including but not limited to: IT, Mathematics, Chemistry, Physics, Engineering, Statistics, Biology/Life Sciences.

Candidates with a background in Computer Science or related areas who are interested in an applied approach to AI are strongly encouraged to apply.

English language

How to apply

Application is through the University’s online form and is currently open. The course code for MSc Applied Artificial Intelligence is P-H60X

You will need to select Department: WMG and tick Type of course: 'Postgraduate Taught' to bring up the full list of WMG courses available for application.

What you will need to provide

• A completed application form and £75 application fee.
• A Personal Statement which can be included in the online application.
• A scan of your transcript (marksheet). If you are still studying, please send us your transcripts to date. NB: if you are made an offer, we will then require you to upload your degree transcripts and certificate in order to clear your conditions.
• English language test result (if applicable) - this can be submitted after you have an offer.
• One reference. If you completed studies less than 2 years ago, this should be an academic reference. If you graduated more than 2 years ago, we will require a professional reference. We contact your referee directly, so please include their valid professional email address on your application form.
• Candidates with professional experience should include their CV with their application.

You can read more about the application process, and access a link to the application form, on our how to apply web page.

Application Deadline

Our official application deadline is 2nd August 2025, however please note that this course will close early if capacity is reached ahead of that deadline. We strongly recommend you apply as soon as you are ready in order to avoid disappointment.

Course Code

The course code for Applied Artificial Intelligence is: P-H60X

Tuition fees

For 2025 entry, the tuition fees are as follows:

• Home students: £12,300
• Overseas students: £35,340

If you are successful in receiving an offer, a deposit payment is required in order to secure your place on the course. Please note that sponsored students can apply for a deposit waiver. For further information, please see our tuition fee deposits pageLink opens in a new windowLink opens in a new windoLink opens in a new windowLink opens in a new windLink opens in a new window

Your remaining tuition fee is then payable at the start of the academic year, or in three instalments. For information about how to pay your tuition fees, please review the University's finance web pagesLink opens in a new windowLink opens in a new windowLink opens in a new windowLink opens in a new windowLink opens in a new window.

WMG Excellence Scholarships

At WMG, we invest more than £1.5 million per year into supporting our talented students and creating a diverse and inspiring learning environment.
Our funding opportunities range from the competitive merit-based WMG Excellence Scholarship open to all offer-holders, through to guaranteed bursaries for specific countries and partnership awards with third-party funders.

WMG Excellence Scholarships are merit-based awards, available on a competitive basis. Awards range from £5,000, £10,000 to £15,000 tuition fee discount.

Applications will be judged on past academic achievement, professional experience, reasons for study, and your vision for the future. View our WMG Excellence Scholarship pageLink opens in a new windowLink opens in a new windoLink opens in a new windowLink opens in a new windowLink opens in a new window for full details on how to apply for this award.

Additional Scholarship opportunities

You might also be eligible to apply for other scholarships from the University of Warwick, such as the Warwick Taught Masters Scholarship Scheme; as well as awards from external funding bodies, including Chevening Scholarships. For additional funding opportunities and eligibility details, please visit the University Funding web pageLink opens in a new window.

Employability and career prospects

As a graduate of MSc Applied Artificial Intelligence, you will typically progress into a career with a focus on data analysis, machine learning, AI development, robotics, automation, natural language processing, or ethical AI. You will be well-prepared to work across a breadth of different industries from manufacturing through to healthcare, education, and finance, and within a range of organisations from large multinational corporations to innovative start-ups.

Potential roles include:

• Data Scientist: Analysing and interpreting complex datasets to help organizations make data-driven decisions.
• Machine Learning Engineer: Designing, building, and deploying machine learning models.
• AI Software Developer: Developing software solutions that incorporate AI and machine learning technologies.
• Robotics Engineer: Working on the design and development of robotic systems.
• AI Product Manager: Overseeing the development and deployment of AI products.
• AI Solution Architect: Creating and implementing AI solutions tailored to specific business needs.
• Natural Language Processing (NLP) Specialist: Focusing on the interaction between computers and human languages.
• Ethical AI Specialist: Ensuring that AI technologies are developed and used responsibly.