Develop robust, reliable and explainable mathematical models and machine learning algorithms for analyzing data arising in diverse applications.
In our increasingly digital world, data is everywhere. It’s in your social network timeline, in your fitness tracker, in MRI scans or in the transactions of a bank. These huge amounts of data are full of valuable information, but extracting that information so that you can put it to good use, can be extremely complicated. It is for good reason that data science is often referred to as a black box: very often there is a lack of explainability and transparency of the algorithms used. In the specialisation in Mathematics of Data Science, you will aim to open this black box and learn to fundamentally understand, improve and develop mathematical models and machine learning algorithms that are essential for analysing data in a wide variety of fields.
What is Mathematics of Data Science
If you’re interested in gaining a fundamental, mathematical understanding of data science, this specialisation is right for you. You will learn how to use the underlying theory from, for instance, statistics, functional analysis or graph theory, to optimally employ and further develop the field of data science. This specialisation will enable you to pinpoint complex problems that occur in certain algorithms and fix them. Eventually, your knowledge of data science will continue where that of non-mathematical data scientists ends.
With your ability to understand and develop reliable, robust mathematical methods, you will be a great asset to many organisations in a variety of fields. Your knowledge will be particularly relevant in sectors where inference from data should be combined with underlying mathematical structures and models, as is the case in companies employing digital twins technology and in medical imaging applications. Explainability and robustness guarantees are crucial for many sensitive use cases, such as personalized patient diagnoses and other medical applications. Besides, more classical data science applications will also be 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, to large-scale industrial applications like predicting power consumption for the optimisation of energy distribution.
What will you learn?
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.
Other master’s and specialisations
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:
- Master’s in Business Information Technology - specialisation Data Science & Business
- Master’s in Computer Science - specialisation Data Science & Technology
- Master’s in Electrical Engineering - specialisation Computer Vision & Biometrics