Advanced Analytics – Big Data

The Warsaw University of Economics offers a second-cycle Master’s course in Advanced Analytics – Big Data, which is aimed at providing students with advanced knowledge and competencies in the field of data extraction and analysis from various sources. The course is designed for students who possess technical and analytical skills, particularly in programming languages such as Python or R and mathematics, including linear algebra, mathematical analysis, and probability theory.

The course curriculum is structured in such a way that students can learn technical skills and data analysis techniques from scratch. While prior knowledge of programming and data analysis can be an advantage, it is not a prerequisite for admission to the course. The curriculum includes classes that cover a wide range of topics such as data analysis, algorithms based on mathematics, and systems/platforms of data analysis. The course also provides opportunities for students to fill any learning gaps through additional courses related to the Master’s course.

The course is designed to prepare students for a variety of career paths in both domestic and international labor markets. Graduates of the program can work in various sectors such as social, economic, business, government, local government, non-governmental (NGO’s), science and education, non-profit organizations, corporations and international organizations. They can work in analytical, consulting, ICT, insurance, banking, and telecommunications companies, among others. The course also prepares students for research work and to undertake third-cycle studies.

The Master’s course in Advanced Analytics – Big Data is a full-time program and lasts for two years, comprising four semesters. The course provides students with the opportunity to develop advanced analytical and technical skills, making them highly competitive in the job market. The course is an excellent opportunity for students who wish to specialize in data analytics and work in fields that require proficiency in data analysis, programming, and mathematics.