This course provides an introduction to data science as a profession and focuses on the theoretical methodologies of the most widely applied machine learning models. The main topics covered include: data preparation (data mining, cleaning and exploring strategies), statistical modeling with the application of appropriate machine learning methodologies (data segmentation, predictive analytics), and mathematical evaluation (test-train split and accuracy measures).
Prerequisites: Statistics and Econometrics at introductory levels, experience with at least one programming language for statistical data analytics (Python, R, or others).
Main instructor of the course is Vahan Sargsyan, Ph.D. is a full time Data Scientist working with big data and implementing machine learning technologies in a cloud-based computer software company. He received his Ph.D. from CERGE-EI in 2019 and also holds a Master degree in Economics from the International School of Economics at TSU, Georgia, and a Master degree in marketing from the Armenian State Agrarian University, Armenia. Vahan also held a 6-month traineeship at the European Research Council Executive Agency (ERCEA) in 2017-2018, where he was enrolled in data analytics and scientific evaluation of research applicants. During his Ph.D. studies, his research was focused on empirical economics, migration and labor economics, specializing in work discrimination.
Classes will start on March 6 and will last till April 14, 2023.
Detailed syllabus of the course is available here!
To take part at this course please fill in the electronic application (opens in new window)!
Application deadline: February 20th, 2023 by 12:00 h (noon).
For additional information contact us at email@example.com or call +385 21 430 706.