Are you excited by the rapid advancements in big data, predictive analytics, and AI technologies such as ChatGPT? Are you looking to study a subject that can unlock tremendous social and economic benefits and is highly sought after by employers?
Key Facts
Why Choose Data Science?
- This programme is designed to take advantage of the growing demand for data scientists across almost every industry sector today including energy, finance, health, government, retail, mining and manufacturing.
- We go beyond classical software engineering, user experience, statistics and data analysis to teach students how to apply logical thinking, machine learning and computer algorithms to come up with solutions to problems faced across many academic disciplines and industry sectors.
- This programme integrates rigorous mathematical training including calculus, algebra, probability, linear algebra, and differential equations with core computing skills in programming, software engineering, and database management.
- We have strong links with industry organisations who support our teaching through case studies within lectures and seminars and prizes (including for example Amazon, CGI and ScotlandIS).
- You will learn both the theory and the practice of data science with special emphasis given to Artificial Intelligence Systems and Knowledge Technologies. We also focus on developing your teamwork, leadership and entrepreneurship skills in preparation for your career.
- The University of Aberdeen is a member of the Turing University Network, a network of UK universities engaged in cutting-edge teaching and research in data science and AI.
What You'll Study
The information on this page is provided for general guidance. While the University of Aberdeen makes every effort to ensure that all course options are available as described, specific courses and content may be subject to change without notice.
Data scientists combine advanced mathematical, statistical, and computational skills to solve complex problems in fields as varied as climate change mitigation, medical diagnosis, process optimisation, and customer experience enhancement.
Recent advances in big data, predictive analytics, and AI technologies such as ChatGPT have transformed how organisations automate processes, forecast trends, and engage with customers. Yet the sheer scale and complexity of modern datasets demand professionals who can not only build systems but also apply mathematical modelling and statistical reasoning to extract meaningful, reliable insights.
Our BSc Data Science is designed to meet this demand. You will develop technical expertise in programming, data management, and distributed systems alongside advanced capabilities in mathematical modelling, statistical analysis, and algorithm design, equipping you for specialist roles in AI, machine learning, deep learning, and cybersecurity. Courses in nonlinear dynamics, chaos theory, and modelling theory further sharpen your analytical edge, enabling you to tackle challenging real-world datasets with precision and creativity.
Unlike some standard Data Science degrees, this programme combines rigorous mathematical training with core computing skills in programming to prepare you for high-demand careers that require advanced analytical and modelling expertise, from data scientist and quantitative analyst to AI engineer and risk modeller.
Throughout the programme, you’ll also explore the ethical and legal frameworks surrounding data use, and learn how to clearly communicate data-driven solutions to technical and non-technical audiences—preparing you for high-demand roles in sectors from technology and finance to healthcare and energy.
- Year 1
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- Algebra (15 credits)
- Calculus I (15 credits)
- Calculus II (15 credits)
- Modelling and Problem Solving for Computing (15 credits)
- Object-Oriented Programming (15 credits)
- Programming (15 credits)
- Understanding Data (15 credits)
- Web Development (15 credits)
- 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)
Careers and Employability
Data Science is one of the most in-demand and fastest-growing fields globally—and the trend shows no signs of slowing down. According to the World Economic Forum's Future of Jobs Report 2025, technology-driven roles top the list of emerging careers, with Big Data Specialists, AI and Machine Learning Experts, Fintech Engineers, and Software Developers leading the way.
Graduates of this programme will be well prepared to enter a wide range of high-growth, high-impact roles across sectors such as finance, healthcare, technology, energy, consulting, and government.
These include:
- Data Analyst: interpreting complex data to support business decision-making
- Data Scientist: applying machine learning, AI, and statistical modelling to uncover insights
- Machine Learning Engineer: building and deploying intelligent systems that learn from data
- AI Specialist: designing smart applications across sectors like healthcare, automotive, and fintech
- Data Engineer: developing and managing infrastructure to store, process, and analyse large data sets
- Quantitative Analyst: using data modelling and statistics to inform financial and investment strategies
Entry Requirements
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Higher Secondary School Certificate (India): a minimum of 75% overall at Standard XII, with a minimum of 80% in English at Standard XII and a minimum of 75% in any two Mathematics or Science subjects at Standard XII
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A-Levels: BBC. Requires any two Mathematics or Science subjects
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IB: 32 Overall, with 5, 5, 5 at Higher Level. Requires any two Mathematics or Science subjects at Higher Level
Want to know more?
Scholarships and Funding
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Details of scholarships and funding opportunities for our Mumbai campus will be announced soon.
How to Apply
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Full details of the application process for our Mumbai campus will be available soon. Please check back for updates.