About this learning event

This event is organized as a blended learning program where participants will first undergo online Python training focused on data manipulation and analysis, followed by a 3-day collaborative coding challenge to implement a solution that helps Central Banks or other regulatory and financial institutions in measuring and mitigating risk. Using open-source datasets, individuals/teams will work on quantifying credit risk by analyzing client portfolio data, calculating the probability of default, as well as other indicators of financial risk. Beyond technical skills, participants will develop problem-solving abilities, critical thinking, creativity, teamwork, and time management.

The blended learning approach will allow participants to first get acquainted with the Python programming language, understanding how to use the various features that it offers for the visualization and analysis of data. Afterwards, during the in-person hackathon, they will be able to apply newly acquired Python skills to real-world data and creatively develop a product that they can use in their own institutions.

Faculty

This learning initiative will be designed with data scientists from the CEF pool of experts and experts from Data science center from DeNederlandisheBank.

• Iman P.P. van Lelyveld, DeNederlandisheBank
• Michiel Nijhuis, DeNederlandisheBank
• Alexandru Monahov, Expert Adviser, National Bank of Moldova
• Benjamin Steiner, IT Specialist, CEF

Target audience

Primariliy data scientists from central banks in South East Europe are invited. Also data scientists from ministries of finance are welcome to join.

Partners

This learning initiative is supported by: