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Data plays a vital role in every private and public sector enterprise: understanding how to use data to inform decision-making has never been more critical. This degree equips you with the skills to explore and analyze complex data sets. And to solve practical problems using applied mathematics, statistics, and computing. You’ll gain a good grounding in mathematical and statistical methods, which provide the foundation for data analysis. Additionally, you’ll learn relevant computing skills, including machine learning and artificial intelligence elements, and gain experience using statistical software. In a world increasingly turning to data for decision-making, there’s a high demand for data scientists in various sectors, including commerce, finance, health, and information technology.
Develop familiarity with mathematical, statistical, and computational data modeling techniques.
Build your software expertise, including the widely used Python and R languages.
Gain experience in communicating and critically commenting on data analysis results.
Increase your employability – data scientists are highly sought after in many sectors.
There is no formal pre-requisite study, but you must have the required mathematical skills to study the compulsory module Essential Mathematics 1 (MST124), including:
algebraic manipulation and solving equations
quadratics and parabolas
geometry and trigonometry
exponentials and logarithms.
In a distance learning course, there are typically no strict regulations regarding part-time employment, providing students with the flexibility to pursue work opportunities while studying remotely. This autonomy allows individuals to manage their schedules and balance professional commitments with their educational pursuits.
Introducing statistics
Introduction to computing and information technology 1
Essential mathematics 1
Introduction to computing and information technology 2
Analysing data
Algorithms, data structures, and computability
Mathematical methods
Practical modern statistics
Applied statistical modelling
Machine learning and artificial intelligence
You'll choose two from:
Applications of probability
Computational applied mathematics
Data management and analysis
Graphs, games, and designs
Interaction design and the user experience
Mathematical statistics
This subject has no language prerequisite.
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