Econometrics and Data Science

Harness the power of data to analyze economic trends and solve complex problems with the University of Amsterdam’s BSc in Econometrics and Data Science. This three-year, full-time program equips you with a powerful combination of economic expertise, statistical analysis skills, and programming proficiency, preparing you for a thriving career in the data-driven world.

Develop a Strong Foundation: Gain a solid understanding of core economic principles, econometric theory, and statistical methods. Master crucial mathematical tools like calculus, linear algebra, and probability theory.

Unlock the Power of Data Science: Learn to collect, clean, analyze, and interpret vast datasets using industry-standard programming languages (Python, R) and statistical software (Stata, SAS). Build machine learning models and leverage data visualization techniques to extract meaningful insights.

Bridge the Gap Between Economics and Data Science: Learn to apply your data science skills to real-world economic problems. Explore topics like econometrics, financial modeling, economic forecasting, and data-driven decision making in the economic sphere.

Project-Based Learning: Develop your analytical and problem-solving skills through engaging projects that combine economic theory with data analysis. Work on real-world case studies, collaborate with professors on research projects, and gain valuable experience applying your knowledge to solve complex economic issues.

Professional Preparation: Refine your communication, teamwork, and critical thinking skills, essential for success in today’s data-driven job market. Learn about career opportunities in econometrics, data science, and related fields.

This program is ideal for students with a strong quantitative aptitude, an interest in economics, and a passion for data analysis. Graduates emerge as versatile econometricians and data scientists prepared for diverse careers in various fields, including:

• Economic research and consulting
• Financial modeling and risk analysis
• Business analytics and data management
• Marketing research and consumer behaviour analysis
• Government agencies and policy analysis
• Data science roles in various industries (tech, healthcare, etc.)