The MSc Artificial Intelligence for Engineering at the University of Hull is a full-time 1 Year Postgraduate program in the field of Engineering. Delivered at the University's Cottingham Road campus in Hull, United Kingdom, the course offers a balanced mix of academic study and practical experience.
Ideal for Bangladeshi students and other international applicants, this program provides high-quality education at a full-time competitive international tuition fee of £ 15,000 Starting each January, September, it is designed to equip students with essential skills for advanced study and professional growth.
The University of Hull offers modern facilities and a supportive environment, ensuring international students receive the guidance and resources needed for success. With a welcoming campus community and dedicated support services, Bangladeshi students can confidently plan their study abroad journey in the United Kingdom through this program.
Course Highlights
Engineering is being increasingly married up with data analytics and driven by artificial intelligence. In this MSc, you will learn how to enhance the command and control of engineering systems in order to optimize them and be a part of the fourth industrial revolution. Understanding how to analyse, validate and interpret data to inform decision-making are key skills in just about every walk of life. Nationally, there is a widely recognised shortage of qualified Artificial Intelligence (AI) and data scientists to meet the needs of industry. This course will equip you with the skills and professional insight needed to launch a career in this fast-growing sector.
The programme will cover topics such as, programming, statistics, machine learning, data visualisation and computer vision and the ethical and legal responsibilities of using data. This engineering variant will include bespoke modules covering deep reinforcement learning, data-driven control with real-world engineering challenges and numerical methods for engineering.
In the third semester, you will have the opportunity to choose or design your own research project in a disciplinary area which may relate to your background or career goals. Alternatively, there may also be opportunity to undertake a project working with an industry partner.
Course Modules
- Programming for AI and Data Science
- Compulsory - 20 Credits
- Fundamentals of Data Science
- Compulsory - 20 Credits
- Understanding Artificial Intelligence
- Compulsory - 20 Credits
- AI for Marketing and Sales
- Compulsory - 20 Credits
- Big Data for Business
- Compulsory - 20 Credits
- Research and Application in Artificial Intelligence and Data Science
- Compulsory - 20 Credits
- Research Project
- Compulsory - 60 Credits
Learning Structure
You will study 180 credits over the duration of your course and be taught in DAIM, a centre of excellence created for this course, drawing on expertise from across the whole University.
The course is taught by experts in Artificial Intelligence and data science with backgrounds in electrical engineering, mathematical modelling, scientific computing and more, as well as highly-cited researchers and brilliant teachers with fellowships of Advanced HE. You'll experience hands-on learning in our 4.5million GBP teaching facility.
Entry Requirements
- A 4-year Honours degree (or equivalent) in a numerical STEM subject (e.g. Sciences, Tech, Engineering, Mathematics, Physics, Chemistry, etc) with CGPA 2.75 or 55% of marks (or above) from recognised institution.
English Language Requirements
Documentary Evidence List
- Academic transcripts (Bachelor degree)
- Degree certificate
- English test (IELTS/ TOEFL/ PTE/ Duolingo - UKVI accepted)
- Statement of Purpose (SOP)
- 2 Recommendation Letters (LORs)
- Updated CV/ Resume
- Research Proposal (for Research/ PhD)
- Work experience certificate(s) (if study gap)
- Passport copy
Study Gaps
For applicants with an academic or professional gap of up to 5 years, admission is generally considered acceptable. If the gap exceeds this period, applications may still be successful but will typically be assessed on a case-by-case basis.
To strengthen your profile, it is important to:
- Provide a clear explanation of how you spent the gap period (e.g., employment, further learning, personal responsibilities).
- Emphasize the skills and experiences you developed during this time that are relevant to the program.
- Demonstrate that your academic qualifications continue to meet the course entry requirements.
Disclaimer: The information provided on this page is sourced from the official university website. Please note that universities may update their course details, fees, entry requirements and any other related information at any time without prior notice. We recommend verifying the latest updates directly with the university.
Last reviewed on 10 September 2025.