Artificial Intelligence is reshaping how organisations analyse data, make decisions, and automate complex tasks. This one-year master’s blends research-led learning with practical projects to help you design intelligent, ethical, and scalable systems. With small classes, lab training, and expert mentorship, you’ll graduate ready to drive innovation in technology and research.
Artificial intelligence today is as much about understanding people as programming machines. This master’s explores how human reasoning, data, and computation combine to create intelligent outcomes. At the University of Aberdeen, Mumbai, students experiment with real datasets, emerging technologies, and the ethics of automation, learning to innovate responsibly and use AI to build smarter systems and stronger societies.
At a glance
What you'll study
Reflecting the structure and standards of the University of Aberdeen’s home campus in Scotland, the programme integrates scientific rigour, analytical training, and ethical awareness.
The MSc Artificial Intelligence at the University of Aberdeen, Mumbai is a concentrated one-year programme combining advanced computational training with hands-on problem solving. Students explore core principles in learning algorithms, data processing, and model design, and apply their knowledge to practical AI solutions in dynamic contexts.
- Semester 1
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Symbolic AI (15 credits) - CS502K This course presents the fundamental techniques of Artificial Intelligence, used in system such as Google Maps, Siri, IBM Watson, as well as industrial automation systems, and which are core to emerging products such as self-driving vehicles. This course will equip the student to understand how such AI technologies operate, their implementation details, and how to use them effectively. This course therefore provides the building blocks necessary for understanding and using AI techniques and methodologies. Machine Learning (15 credits) - CS5062 This course will deliver the most sophisticated Machine Learning methodologies and algorithms which would be illustrated across a wide range of applications including but not limited to images, videos, health, time series data, language processing, etc. This course provides students with the Machine Learning principles for continuing learning and working in the area of Data Science and Artificial Intelligence. Evaluation of AI Systems (15 credits) - CS5063 One of the biggest challenges in Artificial Intelligence is evaluating how well AI systems work. This course will provide students of our MSc in AI with knowledge of core evaluation concepts, approaches, tools, techniques and technologies; we will also look at software testing of AI systems. Applied Artificial Intelligence (15 credits) - CS5079 This course will allow students to use cutting-edge AI technologies to investigate the creation and application of AI systems. Such tools include deep learning libraries and simulation environments. - Semester 2
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Knowledge Representation and Reasoning (15 credits) - CS551J Recent advances in AI have changed the perception of what machines can do, from on-line search to answering questions. An underlying feature of many AI systems concerns how knowledge is acquired, represented, and reasoned with. Companies such as Google, IBM, and Facebook have been developing sophisticated tools for knowledge representation and reasoning. This module provides the theory and practice of knowledge representation and reasoning, also presenting cutting-edge technologies, libraries and tools. At the end of the course students will be able to design, implement and evaluate knowledge-intensive AI systems. Software Agents and Multi-Agent Systems (15 credits) - CS551K The global autonomous systems market is expected to be valued at over £13 billion by 2025, involving both software systems and robots. Such autonomous systems act to achieve goals with no human intervention, and are already found in Tesla's self-driving cars, NASA space probes and systems such as Amazon's Echo. This course provides the student with a solid grounding in the theory and tools which underpin such systems, teaching them both how to develop such systems, and use them effectively as part of a larger product. Data Mining with Deep Learning (15 credits) - CS552J This course aims to make students familiar with basic data mining and visualisation techniques and software tools. Students will learn how to analyse complex datasets by applying data pre-processing, exploration, clustering and classification, time series analysis, and many other techniques. This course will also cover text mining and qualitative modelling. Through this course students will be able to analyse real-world datasets in various domains and discover novel patterns from them. This course is particularly suitable for those who are interested in working as data analysts or data scientists in the future. Natural Language Generation (15 credits) - CS551H The aim of the course is to introduce students who have some background in computing to (1) the varied aims for which Natural Language Generation (NLG) is pursued, (2) the main rule based and statistical methods that are used in NLG, and (3) some of the main NLG algorithms and systems. The course will cover NLG both as a theoretical enterprise (e.g., for constructing models of language production) and as practical language engineering, paying particular attention to the link between NLG and data science. Some programming experience is expected. - Semester 3
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MSc Project in Artificial Intelligence (60 credits) - CS5917 This course will provide students of our MSc in AI programme with the opportunity to develop their own AI research project, under the supervision of a member of staff. Typical projects include extending, improving or adapting existing AI theories or techniques to solve different problems, comparing competing techniques or tools to solve a particular problem, and so on. Students will improve their problem-solving and communication skills, as well as broaden, deepen and consolidate knowledge obtained in other components of the degree.
How you'll study
Learning methods
- Group Projects
- Individual Projects
- Lectures
- Peer Learning
- Research
- Tutorials
- Workshops
The MSc Artificial Intelligence combines hands-on experimentation with research-led learning. You’ll work closely with peers and faculty to tackle real-world challenges using emerging AI tools and frameworks.
Teaching involves a blend of lectures, tutorials, workshops, and group projects designed to strengthen both your technical and analytical abilities. Collaborative exercises encourage critical thinking, creativity, and independent inquiry, ensuring you can translate theoretical knowledge into practical solutions.
Assessment is through coursework, examinations, presentations, and project reports, with regular feedback to support your growth throughout the programme.
Why study MSc Artificial Intelligence?
- This programme bridges the science of intelligent systems with their practical application. It trains you to design, evaluate, and improve AI models that interpret data, make decisions, and solve complex problems.
- You’ll develop hands-on skills in machine learning, symbolic AI, natural language processing, and data mining, guided by faculty with active research in these domains. A capstone research project allows you to test ideas, apply theoretical insights, and demonstrate technical precision.
- The University of Aberdeen is internationally recognised for its contributions to Data Science, Machine Intelligence, and Natural Language Generation, including pioneering work with ARRIA NLG, a world leader in automated language technologies. As part of the Turing University Network, the University of Aberdeen connects students to cutting-edge research and professional collaborations that define the next era of artificial intelligence.
Interested in this programme?
Entry Requirements
Applicants must hold a bachelor’s degree equivalent to a UK 2:2 in computing science or a closely related discipline from a recognised university.
- Key subjects: A background in Python, Algorithmic Problem Solving, and Data Structures is required. Experience with other programming languages such as Java, C, or C++ is recommended, but not mandatory.
India:
Applicants should generally have obtained a minimum overall score as follows:
- 55% or above for graduates from leading institutions such as the University of Mumbai, University of Delhi, University of Calcutta, IITs, or IIMs
- 60% or above from other State or Central Universities
- 65% or above from Private or Deemed Universities
Fees and Funding
Save ₹2000 on your application fee. Apply before 30 June 2026 with zero application fee.
Scholarships
The fee structure at the University of Aberdeen, Mumbai differs by programme and level of study. Detailed information on fees, inclusions, and payment options will be shared to help students and families plan with confidence.
The University of Aberdeen is committed to widening access and supporting students from all backgrounds. Scholarships will include need-based assistance for learners from low-income households and merit-based awards for high-achieving students.
All eligible admitted students joining the 2026–27 intake receive the Aberdeen Pioneer Scholarship, while academically eligible students may also receive the Merit Scholarship based on their Class XII / Grade 12 or equivalent results.
Together, these scholarships provide up to ₹4,50,000 per year towards tuition fees, for every year of your programme, subject to scholarship eligibility. Know more.
Scholarships will include need-based assistance for learners from low-income households and merit-based awards for high-achieving students. Complete details of the fee structure and scholarships will be communicated during the admissions process.
Careers
Artificial intelligence has rapidly advanced in both capability and influence, reshaping how industries operate and innovate. With tools such as generative AI and large language models entering mainstream use, the demand for professionals who can design, manage, and guide these technologies has never been higher.
Governments and enterprises worldwide are investing in AI leadership, reflecting its growing strategic importance.
The MSc Artificial Intelligence at the University of Aberdeen, Mumbai equips graduates with the expertise to thrive in this expanding field. Through advanced training in machine learning, natural language processing, symbolic AI, and data mining, you will develop the ability to design intelligent systems and translate AI theory into practical innovation.
Students benefit from the University of Aberdeen’s partnerships with the Centre for Data and Artificial Intelligence and the Turing University Network, connecting them to leading developments in AI and data science.
Career opportunities:
- AI Engineer
- Machine Learning Engineer
- Data Scientist
- NLP Specialist
- Robotics Engineer
- Computer Vision Engineer
- AI Consultant
- Research Scientist
Accreditation
The University of Aberdeen is a globally recognised Scottish institution with a tradition of excellence dating back to 1495. Ranked among the top universities in the world, it upholds a strong reputation for research-led teaching and interdisciplinary innovation.
All programmes at the Mumbai campus follow the same academic regulations, governance processes, and assessment standards as those delivered in Scotland, ensuring students earn an identical UK degree awarded by the University of Aberdeen.