A 4-day training school on deep learning in digital finance, featuring hands-on LLM sessions, ethics and policy discussions, and career development, by the Atlantic coast in Portugal. GPS: 40.152329, -8.858540

Courses offered: Blockchains in Digital Finance (4EC, ASE) HE framework and research project management (1EC, ASE)

How should we invest in a world of uncertainty, sustainability challenges, and responsibility toward future generations?

Join leading experts from Cardo AI for an intensive course on some of the main machine learning use cases in the Financial Services Industry, with an emphasis on Credit Markets and Structured Finance.

Organized by the Bucharest University of Economic Studies (ASE)

In this training week, participants will attend two accredited courses totaling 4 ECTS: History and Prospects of Digital Finance (3 ECTS) and Environmental Aspects (1 ECTS).

The Second AI in Financial Markets Research Forum serves as a knowledge exchange platform between industry representatives from finance and academia in the field of AI, Digital and Sustainable Finance, with a focus on generative AI models.

This intensive program (3EC) is designed to equip participants with the skills to develop AI agents using OpenAI APIs, with a strong emphasis on Retrieval-Augmented Generation (RAG) techniques and agentic architectures.

I. Introduction to Blockchain applications in finance (ASE) II. Scientific Writing (BFH)

The course provides a comprehensive introduction to Explainable Artificial Intelligence (XAI), emphasizing the methodologies and practical applications of cutting-edge models such as LIME, SHAP, deep learning XAI, time series-based XAI methods and others.

Pillar II. Green Digital Finance (3/3EC, KTU) Pillar I. Ethics Applicable to Digital Aspects (2/4EC, UTW)

In this lecture, Prof Dr Wolfgang Haerdle will focus on spectral risk measures and spectral analysis.

1 MSCA DIGITAL Research Day 1 MSCA DIGITAL Mid-Term Meeting (MTM) 3 days of Technical Training Attendance to the Mid-Term Meeting is mandatory for DCs, as well as for at least one (1) representative per member of the MSCA DIGITAL Industrial Doctoral Network.