Selected Topics in Supervised and Unsupervised Machine Learning


Gain working knowledge of the main classes of machine learning algorithms through R applications. The course will cover both unsupervised as well as supervised ML techniques, placing focus on their utility tackling various economic and financial questions. Applicability and limitations will be at the forefront of the conceptual discussion, followed by R-based code-along. Time permitting, selected Bayesian Models will be discussed.


Will be interesting for

  • Analysts working at public sector organizations and research centers, students, professors, and scientists.


After course completion, you will be able to

  • To employ and test a number of standard ML models for forecasting and economic analysis. The focus is on macro and microeconometrics applications both in the time domain as well as in the cross-section (analyzing decisions of firms, households, etc.)



Basic calculus and linear algebra; basic R



Mihnea Constantinescu – PhD from the University of Zurich.





Education format

Twice a week for seven weeks



Monday, March 6 through Friday, 28 April 2023



10 000 uah