BSc (Hons) Data Sciences

The bsc data sciences programme at heriot-watt university positions you at the vanguard of the data analytics and engineering revolution. It enables the transformation of data into actionable insights and equips you to address complex challenges in diverse industries. 

The curriculum lays a robust foundation in mathematics and statistics, emphasizing large-scale data computation with the latest programming languages. Graduates are primed for dynamic roles in sectors such as business, finance, government, science, transportation, forensics, energy, the environment, and research.

In the initial three years, students hone essential skills in mathematics, computer science, probability, statistics, machine learning, and artificial intelligence. The final year offers specializations in advanced machine learning, state-of-the-art statistical algorithms, data engineering, or cutting-edge AI applications. Embark on this journey to lead in the thrilling domain of data science.

The National Robotarium

• Situated at Heriot-Watt University's Edinburgh campus and in collaboration with The University of Edinburgh, innovates solutions for global challenges by partnering with industry to evolve and commercialize robotics, Data Science, AI, and automated technologies.
• It nurtures the education and growth of future roboticists, generating highly competent graduates poised for influential research with a commercial perspective, and devises programs that endow the current and forthcoming workforce with skills in robotics, data, and programming.

The Campbell Maths Gym

• A cross-campus endeavour designed to bolster students' mathematical and statistical abilities and enhance their confidence in these areas.
• Our BSc Data Sciences programme offers a broad spectrum of expertise and research opportunities across various mathematical and Computing disciplines.

These include:

• Advanced Mathematical Theory: Leading the exploration into the fundamental theoretical principles that form the backbone of pure mathematical concepts and applications. Our profound understanding and innovative approaches are setting new benchmarks in the field.
• Applied Mathematics: At the forefront of developing mathematical models to tackle real-world problems. Our pioneering methodologies and solutions are influencing the way the world approaches problem-solving.
• Computational Mathematics: Championing the cultivation of comprehensive numerical and programming skills to decipher complex mathematical models and optimise solutions to real-world problems. Our expertise is shaping the future of computational problem-solving.
• Statistics and Data Analysis: Pioneering the development of crucial statistical and data analysis skills to extract meaningful insights from data sets and inform decision-making processes. Our advanced techniques are setting the standard for data-driven decision making.
• Software Development: Excelling in the design, coding, and testing of software, with a special focus on mathematical applications. Our proficiency and innovative approaches are pushing the boundaries of software development.
• Data Science and Analytics: Leading the way in developing skills to interpret and manage data, using statistical methods and machine learning for informed decision-making. Our cutting-edge techniques are transforming the landscape of data science and analytics.
• Artificial Intelligence: Advancing the understanding of the theoretical foundations of AI and its applications in automating problem-solving. Our insights and innovations are driving the evolution of artificial intelligence.

The BSc Data Science programme offers an outstanding learning environment:

• Departmental Expertise: The programme is delivered by the School of Mathematical and Computer Sciences' three departments: Mathematics, Actuarial Mathematics and Statistics, and Computer Science. This multidisciplinary approach provides a diverse range of expertise to enhance and shape your educational experience.
• Support: Our comprehensive support system assists students throughout their university journey. This includes personal tutors, year coordinators, student officers, and tailored courses designed to smooth the transition from school to university.
• Heriot-Watt's GRID (Global Research, Innovation and Discovery) is a state-of-the-art facility that fosters global research, innovation, and discovery. GRID offers a dynamic teaching and learning space for computing students and houses our pioneering VR Labs and Games Design Studio.
• Industry Links: Our strong connections with the computing industry are evidenced by the participation of over 30 company representatives on our Industrial Advisory Board. Our research often involves collaboration with leading computing firms, and our students highly appreciate the research-driven teaching provided by our passionate faculty.
• Our student equipment fund is an initiative to support students in purchasing technology (either in hardware, data or software) to explore the usage of and code development for new platforms, as part of a taught course or as a personal project.

Course Content
Year 1

• Students will study seven mandatory courses: Calculus A, Praxis, Software Development 1, Calculus B, Discrete Mathematics, Software Development 2 and Introduction to Statistical Science B, as well as one optional course

Mandatory September

• Software Development 1
• Calculus A
• Topics in Statistical Practice

Mandatory January

• Calculus B
• Web Design and Databases
• Software Development 2
• Elements of Probability

Optional September

• Introduction to University Mathematics

Year 2

• Students will go on to study six mandatory courses: Calculus and Real Analysis, Linear Algebra, Probability and Statistics A, Data Structures and Algorithm, Database Management Systems and Probability and Statistics B, as well as one Optional course.

Mandatory September

• Real Analysis
• Algorithmic and Scientific Programming
• Linear Algebra
• Probability and Statistics A

Mandatory January

• Multivariable Calculus
• Introduction to Software Engineering
• Database Management Systems
• Probability and Statistics B

Year 3

• Students will go on to study six mandatory courses: Statistical Machine Learning, Artificial Intelligence and Intelligence Agent, Software Engineering, Advanced Statistical Methods, Professional Development, Bayesian Inference and Computational Maths, as well as two Optional courses.

Mandatory September

• Statistical Models A
• Artificial Intelligence and Intelligent Agents
• Software Engineering
• Further Statistical Methods

Mandatory January

• Professional Development
• Statistical Models B
• Bayesian Inference & Computational Methods

Optional January

• Ordinary Differential Equations

Year 4

• In Stage 4, students complete an individual disseration (30 credits) and take four mandatory taught courses. In addition, in each semester, students can choose one optional course that is aligned with their own particular interests.

Mandatory September

• Dissertation A
• Time Series and Machine Learning

Optional September

• Software Engineering Foundations
• Optimisation
• Numerical Analysis C

Mandatory January

• Big Data Management
• Dissertation B
• Advanced Machine Learning

Optional January

• Numerical Analysis D
• Climate Change and Sustainability