Big Data Science Kozminski University

Overview

Our Master in Big Data Science from Kozminski University is a two-year, English-taught programme that equips students with in-demand skills in Big Data, AI, and Machine Learning, with a strong focus on Finance and Health Economics and applications across multiple industries. The curriculum emphasizes advanced data collection methods, data analysis, machine learning, and AI, ensuring a deep, practical understanding of modern data-driven technologies.

Delivered full-time in evening hours (17:00–21:00), the programme is designed for students who want to combine professional work with graduate studies. Students choose between two majors - Data Analytics or Health Economics & Big Data Analytics - and gain additional expertise in entrepreneurship, venture capital, and cloud computing, preparing them to become not only skilled analysts but also future leaders and innovators in tech-driven sectors.

Programme Highlights

• Intensive, hands-on and meritocratic programme - From the first semester, students combine advanced mathematics and statistics with hands-on practice. Graduates are highly valued by top global companies, with alumni in senior roles at firms such as Goldman Sachs, Microsoft, Accenture, and Oracle.
• Learning Data Science and AI using advanced tools
• Students gain skills in R, Python, and major cloud platforms, access top training tools, and receive discounts for Microsoft and Amazon certification exams.
• Wide career opportunities
• The Polish labor market shows strong demand for specialists in AI, Machine Learning, IT, Finance, and Healthcare, with salaries averaging 34% above the national level and demand expected to grow by 14% annually over the next five years.
• Two possible majors: Data Analytics and Health Economics - The Data Analytics major develops advanced Big Data and AI skills for careers in finance and beyond, while the Health Economics & Big Data Analytics major applies these tools to improve efficiency, costs, and resource allocation in healthcare.
• Multiple study resources: access to the largest business and academic databases - Whether focused on practical business problems or academic research, KU provides access to key databases for business and finance, including Reuters, BankScope, EMIS, Infinancials, ScienceDirect, ProQuest, and JSTOR.
• International academic and professional staff - The faculty includes academics - over half with doctorates from top global universities like Oxford, Bocconi, and Wharton - and experienced industry professionals, many holding senior roles at companies such as P&G, Microsoft, and Oracle.
• Training and mentorship possibilities - Kozminski University offers skill development, certifications, and entrepreneurship support via the Business Hub, Venture Capital Fund, and platforms like AWS Academy, Bloomberg, and GitHub. 

• Professional Internship - The 130-hour professional internship (5 ECTS), usually in the 4th semester, lets students apply theory, gain experience, build connections, and develop skills essential for career success and master’s thesis research.

Career Opportunities 

• Big Data Analytics Manager

• Data Solutions Architect

• Business Intelligence Consultant

• Financial Market Analyst

• Analytics Consultant

• Business Analyst

• Business Consultant

• A specialist in any department of a company where knowledge of finance and big data is a must

• An employee of a financial department in an international corporation or a financial institution

• Data Scientist

• Researcher

Program structure

Your Future in Big Data & AI Starts Here!

Gain the skills to thrive in the Healthcare & Financial sectors and beyond with our cutting-edge Big Data Science program. Master AI, Data Analytics, and Machine Learning-all designed for ambitious professionals who want to stay ahead in the digital revolution.

The HEBDA study track is intended for both Polish and international students, reflecting the global nature of contemporary challenges in healthcare. Classes have a distinctly practical focus: students not only learn theory but also work with case studies and real-world data from healthcare systems around the world. Over the course of the programme, participants gain hands-on experience with the tools and methods used by professional health economists and data scientists, including statistical software, programming for data analysis, economic modelling techniques, and data visualisation. This strong practical orientation ensures that graduates are prepared to take up positions requiring data-driven decision-making in health policy, management, strategy, or innovation.