Mathematics of Data Science

‹ Machine Learning for Intelligent Systems Biological Data Analytics ›

Mathematics is ubiquitous in Data Science. Behind a wide number of Data Science models and methods used to handle real-world applications, there are plenty of mathematical tools that make things work.

This curriculum qualifies students to build and analyze structured models for the representation of concrete applications, to properly choose and/or develop methods for the handling of those models, to get a deep understanding of tailored techniques and mathematical theory for data analysis, to combine and redevelop all those tools in order to solve complex problems.

The courses included in the curriculum put an emphasis on notions coming from statistics, machine learning, optimization, and the theory of big data representation.

Click here to find out the details of the study plan!

Requirements

We welcome students with a strong background in mathematics, statistics, and computer science.

Prospective students should have the willingness to study mathematical theory and apply their knowledge in the practical management of big data applications.

More specifically, what we expect from students in the curriculum is that they have an interest in using mathematical tools and tailored algorithms for the analysis of data.

What to expect

This curriculum is conceived as a multi-disciplinary platform that enables students to handle models/methods coming from statistics, machine learning, and optimization and to properly understand the way all those tools are intertwined in big data applications.

Projects and homework will allow the students to develop project management and analytical skills in their areas of interest. The partnerships with industries and research institutions will further enable the student to implement mathematical techniques in the solution of exciting data science applications.

After this two-year program, graduates will understand how to represent, compress and store huge datasets and develop suitable models to recognize and analyze data. They will also get a deep knowledge of methods and algorithms for the proper handling of big data models. Finally, they will have the chance to tackle advanced problems and applications based on current research.

Employment prospects

Companies and Research Institutions that deal with the management and analysis of huge-scale data in, e.g., finance, transportation, communications, and biology are surely interested in data scientists with a strong mathematical background that are able on the one side to approach a real-world problem using computational analysis and on the other side to understand the mathematics underpinning these advanced techniques.

Our graduates, thanks to their deep knowledge of mathematical theory and the ability to deal with the computational challenges behind data-driven systems, hence own an effective and attractive professional profile that surely guarantees an excellent placement in the job market.