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Develop robust, reliable and explainable mathematical models and machine learning algorithms for analysing data arising in diverse applications and building the mathematics behind AI.
Artificial intelligence is moving fast, with new ideas and techniques continually extending the capabilities of existing methods. In our increasingly digital world where data is everywhere, how do we ensure algorithms are robust, reliable, and explainable? The specialisation in Mathematics of Data Science & Artificial Intelligence offers a deep understanding of the algorithms that drive contemporary AI. By combining mathematical depth with practical insight, you will be prepared to turn fundamental ideas into impactful AI systems. You will learn to navigate real-world constraints, scalable algorithms, and large-scale data processing to build the mathematics behind tomorrow’s AI.
When developing algorithms and methods in data science, many intricate choices are to be made. Should we favor performance, or explainability? How much structure should we assume, and how much should we let the data speak for itself? In this specialisation, you will learn how to navigate these questions guided by mathematical principles.
This specialisation takes a two-pronged approach. You will gain a deep understanding of current state-of-the-art techniques – including modern large language models – while looking beyond current trends to grasp the mathematical foundations of modern AI.
You will study theoretical foundations drawing on areas such as statistics, optimisation, deep learning, and reinforcement learning. This enables you to understand not only how methods work, but why they work. You will learn to identify the mathematical structure of complex problems, assess the strengths and limitations of existing methods, and gain the insight needed to analyse, improve, and design new algorithms yourself. Ultimately, this equips you for a wide range of careers, from research and development to advanced industry roles where understanding matters as much as implementation.
With your ability to understand and develop reliable, robust mathematical AI methods, you will be a great asset to companies and organisations across a variety of fields. Your knowledge is especially relevant in sectors where data inference must be combined with underlying mathematical structures, such as in digital twin technology and medical imaging. In sensitive use cases like personalised patient diagnoses, explainability and robustness guarantees are crucial.
Furthermore, more classical data science applications will also be well within your reach. These range from detecting fraudulent transactions in the financial sector to advancing text-based techniques like natural language processing and large language models, or predicting power consumption for the optimisation of energy distribution in large-scale industry.
If you are interested in learning how data science can fundamentally impact healthcare through a hands-on including case studies and a master project close to direct applications, you can choose to focus your specialisation on a specific profile: Artificial Intelligence for Health.
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As a graduate of this Master's and this specialisation, you have acquired specific, scientific knowledge and skills and values, which you can put to good use in your future job.
After completing this Master’s specialisation, you:
After successfully finishing this Master’s specialisation, you:
Is this specialisation not exactly what you’re looking for? Maybe one of the other specialisations suits you better. Or find out more about these other related Master’s: