Data science is the core of the modern data analytics and engineering revolution, turning data into intelligence and information for decision-making and for solving complex, multi-faceted problems. It is a young discipline, and demand for expertise in all aspects of data science is growing very quickly. Because of this strong global demand, the role of data scientist is frequently ranked as the most promising career and consistently tops the best jobs rankings, with professionals in the field reporting high demand, high salaries and high job satisfaction.
The BSc in Data Sciences programme is based on a strong mathematical and statistical foundation and emphasises large-scale data computation using the most relevant and up-to-date programming languages. Depending on their interests, graduates may find employment in the areas of business, finance, government, science, transportation, forensics, energy, the environment or academic research.
The first three years of the programme are designed to provide the necessary core skills and knowledge in mathematics, computer sciences, probability, statistics, machine-learning and artificial intelligence. The fourth year offers the option to focus on advanced machine-learning, statistical algorithms and applications, data engineering, mathematical aspects of data structures or applications to artificial intelligence.
We pride ourselves in providing students with useful skills both computational and mathematical that can be used to find interesting information in large datasets either statically or dynamically in real time. These skills can be used to find lucrative and interesting jobs in industry and commerce.
We have very strong links with external organisations and industry, with representatives of more than 30 companies and organisations attending our industrial advisory board. Much of our research is in collaboration with leading computing enterprises and students really value our research-led teaching by our enthusiastic staff.
Our Student Lead Technology Club is an initiative to support students in using technology (either 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.
Semester 1
Semester 2
Mandatory courses: Calculus B, Discrete Mathematics, Software Development 2, Intro to Statistical Science B
Semester 1
Mandatory courses: Calculus and Real Analysis A, Linear Algebra, Probability and Statistics A, Introduction to Data Structure and Algorithms
Mandatory courses: Data Structures and Algorithms, Database Management Systems, Probability and Statistics B, Numerical Analysis A
Semester 1
Mandatory courses: Statistical Machine Learning, Artificial Intelligence and Intel Agent, Software Engineering, Advanced Statistical Methods
Semester 2
Mandatory courses: Professional Development, Bayesian Inference and Comp Maths, Data Visualisation Analytics, Statistical Models B
Semester 1
Semester 2
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