I have recently been working as a manager in analytics, having previously worked as a Data Scientist at the same company. The goal of analytics in the economy is always to generate incremental value to the functioning of the organization. Data Science achieves this by applying mathematical algorithms, statistical methods and computing technologies to the available data. It is about an interesting cohesion of science, technology and economy.

The SAFM course at the Faculty of Mathematics is an ideal place to acquire basic knowledge on which Data Science is based. Deep understanding of random variables, distributions, stochastic processes, statistical evaluation, etc. is clearly applicable in this area. But even on top of that, it would be hard to single out a branch of mathematics that hasn't yet found a way to apply it to machine learning problems. The importance of learning theoretical mathematics itself is huge, because it develops the skills of logical reasoning and analytical problem solving. Finally, the courses where students learn programming are extremely useful. It is possible to be successful as a Data Scientist without detailed knowledge of all the above aspects, but someone who successfully passes MATF has a high chance of becoming respected in this profession. In today's world of astonishing technological development, new learning content is constantly appearing. Each individual ultimately finds their own approach to navigating that world of innovation. Also, learning a lot about the organization's business domain is a necessity in the Data Science profession. That's what awaits you after college. What fulfills me in my daily work is the creative process. Starting from a given problem, it is up to me to design a solution methodology that relies on some theoretical knowledge applied to concrete data; then I move on to the engineering work of implementation in the form of program code and design of system automation. What fulfills me in my daily work is the creative process. Starting from a given problem, it is up to me to design a solution methodology that relies on some theoretical knowledge applied to concrete data; then I move on to the engineering work of implementation in the form of program code and design of system automation. What fulfills me in my daily work is the creative process. Starting from a given problem, it is up to me to design a solution methodology that relies on some theoretical knowledge applied to concrete data; then I move on to the engineering work of implementation in the form of program code and design of system automation.

For many of us, the student period was not easy. As a reward for the persistence and perseverance that we then show, paths to success open up that can mark the entire professional life. Dear future and current students, someone wise once said ‘A smooth sea never made a skilled sailor.’