The BSc (Hons) Data Science at the University of Aberdeen, Mumbai, is a four-year undergraduate programme for students eager to master data analytics, programming, and mathematical modelling. It equips you with the skills to analyse complex datasets, design algorithms, and extract reliable insights that drive decisions across fast-growing sectors such as technology, finance, energy, healthcare, and government, preparing you to meet the global demand for professionals who can integrate mathematics, statistics, and computing to solve real-world problems with clarity and precision.
Data underpins automation, prediction, and innovation in every modern industry. The BSc (Hons) Data Science prepares you to work at the core of these transformations, combining advanced training in mathematics, programming, and data management. Unlike traditional data science degrees, it offers rigorous mathematical and statistical foundations alongside computing expertise, helping you understand, model, and manage complex real-world datasets with precision and creativity.
At a glance
What you'll study
The programme combines mathematical depth with computational strength. You will develop technical expertise in programming, data management, and distributed systems, together with advanced abilities in mathematical modelling, statistical analysis, and algorithm design.
Through nonlinear dynamics, chaos theory, and modelling theory, you begin to see how small changes can shape significant outcomes. These subjects train you to recognise hidden structures, evaluate uncertainty, and work comfortably with intricate mathematical models; skills that carry weight across advanced study and applied quantitative fields.
You will also explore the ethical and legal frameworks governing data use and learn to communicate technical insights clearly to varied audiences. By the end of the degree, you will be able to use mathematics, statistics, and computing to address real-world challenges across sectors spanning technology, finance, healthcare, energy, etc.
- Year 1
-
Term 1
Algebra (15 credits) - MA1006 This course introduces the concepts of complex numbers, matrices and other basic notions of linear algebra over the real and complex numbers. This provides the necessary mathematical background for further study in mathematics, physics, computing science, chemistry and engineering. Modelling and Problem Solving for Computing (15 credits) - CS1029 This course will introduce students to techniques that support problem solving and modelling with computers, and concepts and methods that are fundamental to computing science. The techniques and concepts will be illustrated with numerous computing examples. Programming 1 (15 credits) - CS1032 This course will be delivered in two halves. The first half will provide a self-contained introduction to computer programming. It will be accessible to all undergraduates. Students will be exposed to the basic principles of computer programming, e.g. fundamental programming techniques, concepts, algorithms
and data structures. The course contains lectures where the principles are systematically developed. As the course does not presuppose knowledge of these principles, we start from basic intuitions. The second half will be particularly of use to those studying Science and Engineering subjects, broadly interpreted, as well as Computing and IT specialists. It will include a gentle introduction to professional issues and security concepts.Calculus 1 (15 credits) - MA1006 Calculus is the mathematical study of change, and is used in many areas of mathematics, science, and the commercial world. This course covers differentiation, limits, finding maximum and minimum values, and continuity. There may well be some overlap with school mathematics, but the course is brisk and will go a long way quickly. Term 2
Object-Oriented Programming (15 credits) - CS1527 This course will build on the basic programming skills acquired in the first half-session and equip the students with advanced object oriented programming knowledge, implementation of data structure and algorithms, and basic software engineering techniques. The students will be challenged with more complicated programming problems through a series of continuous assessments. Web Development (15 credits) - CS1534 Students will learn to develop modern web applications using a variety of languages and frameworks as part of their degree, and prepare them for whatever they do after graduation. A key focus will be on the integration of HTML with CSS and Javascript with other backing frameworks to develop dynamic applications. The course is open to all undergraduates, and is accessible to those with no previous experience. Understanding Data (15 credits) - ST1506 This is a statistics course open to all first and second year students. It is a useful course for students whose degree subject involves some amount of statistical analysis. The course teaches students how to summarise data effectively and how to correctly interpret it. Among the topics covered are sampling strategies, probability theory, confidence intervals and hypothesis tests. There are also weekly computer practicals using the statistics software RStudio. The mathematical context is emphasised but students are not expected to have a high level of maths. Calculus 2 (15 credits) - MA1508 The aim of the course is to provide an introduction to Integral Calculus and the theory of sequences and series, to discuss their applications to the theory of functions, and to give an introduction to the theory of functions of several variables.
This provides the necessary mathematical background for further study in mathematics, physics, computing science, chemistry and engineering.
- Year 2
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- Algorithms and Data Structures (15 credits)
- Applied Linear Algebra (15 credits)
- Databases and Data Management (15 credits)
- Dynamical Phenomena (15 credits)
- Human–Computer Interaction (15 credits)
- Probability (15 credits)
- Software Programming (15 credits)
- Statistics (15 credits)
- Year 3
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- Artificial Intelligence (15 credits)
- Differential Equations (15 credits)
- Distributed Systems and Security (15 credits)
- Languages and Computability (15 credits)
- Principles of Software Engineering (15 credits)
- Professional Skills for Sciences (15 credits)
- Software Engineering and Professional Practice (15 credits)
Plus one of:
- Operating Systems (15 credits)
- Robotics (15 credits)
- Year 4
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- Modelling Theory (15 credits)
- Natural Language Processing (15 credits)
- Nonlinear Dynamics and Chaos Theory I (15 credits)
- Research Methods (15 credits)
- Single Honours Data Science Project (45 credits)
Plus one of:
- Data Engineering (15 credits)
- Financial Mathematics (15 credits)
- Introduction to Machine Learning and Data Mining (15 credits)
How you'll study
Learning methods
- Lectures
- Seminars
- Case Studies
- Written Exams
- Dissertation
Students are assessed through a combination of coursework, practical evaluations, and written examinations. Coursework includes essays, reports, and data-based assignments completed during each semester.
Practical assessments test technical proficiency, while written exams evaluate theoretical understanding. In the final year, your Honours Project will be assessed through a written dissertation.
Why study BSc (Hons) Data Science?
- This programme is designed to meet the growing demand for skilled data scientists across industries such as energy, finance, healthcare, government, retail, mining, and manufacturing.
- It combines rigorous mathematical training in calculus, algebra, probability, linear algebra, and differential equations with strong computing foundations in programming, software engineering, and database management.
- Our programme is supported by industry collaborations with organisations such as Amazon, CGI, and ScotlandIS, offering real-world case studies, guest lectures, and student awards.
- It features modules in Artificial Intelligence Systems and Knowledge Technologies, blending theory with hands-on application.
- Our programme also emphasises teamwork, leadership, and entrepreneurship skills to prepare students for collaborative, high-impact roles.
- We encourage an understanding of ethical and legal frameworks that govern modern data use.
- As part of the Turing University Network, the University of Aberdeen connects you to leading UK research and innovation in data science and AI.
- Provides a balance of theory and practice, ensuring graduates are well-positioned to launch their careers in this increasingly data-oriented economy.
Interested in this programme?
Entry Requirements
Indian boards (CBSE/ISC/State boards):
A minimum of 75% overall at Standard XII, with a minimum of 80% in English at Standard XII and a minimum of 75% in either Mathematics OR two Science subjects at Standard XII.
International students:
Applicants must hold either of the following:
- A Levels (UK/Cambridge): Minimum BBC, including any two subjects in Mathematics or Science.
- International Baccalaureate (IB): Minimum 32 points overall, with 5, 5, 5 at Higher Level, including any two Higher Level subjects in Mathematics or Science.
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
India is emerging as a global hub for data analytics, with increasing demand for professionals skilled in data management, artificial intelligence, and machine learning across all sectors. Also, according to the World Economic Forum’s Future of Jobs Report 2025, technology-driven roles such as Big Data Specialists, AI and Machine Learning Experts, Fintech Engineers, and Software Developers are among the fastest emerging careers. Graduates of this programme will be equipped with strong analytical, computational, and problem-solving skills that are highly valued across various sectors, including finance, healthcare, technology, energy, consulting, and government.
Career paths include:
- Data Analyst
- Data Scientist
- Machine Learning Engineer
- AI Specialist
- Data Engineer
- Quantitative Analyst
Beyond these roles, the programme also opens pathways to advanced academic and research opportunities in data science, artificial intelligence, and related disciplines. Whether you aspire to innovate in industry or pursue cutting-edge research in academia, the BSc Data Science degree gives you the versatility and depth to shape your future on your own terms.
Accreditation
Founded in 1495, the University of Aberdeen is the third-oldest university in Scotland and the fifth-oldest in the English-speaking world. It is ranked 12th in the UK by the Guardian University Guide 2025 and 15th in the UK by the Times and Sunday Times Good University Guide 2025. The University is also ranked 3rd in Scotland for Overall Student Satisfaction in the 2025 National Student Survey (NSS). With a legacy of excellence in teaching and research, the University counts several Nobel Laureates in STEM disciplines among its distinguished alumni, faculty, and researchers.
At the University of Aberdeen Mumbai, you will study under the same academic standards and with the same commitment to excellence that define the institution’s global reputation.