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Agentic AI for Finance - Training Week

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.

Agentic AI for Finance - Training Week
Agentic AI for Finance - Training Week

Time & Location

01 Dec 2025, 09:00 – 03 Dec 2025, 17:00

Seminar Room EG 1, RBI Head Office, Am Stadtpark 9, 1030 Wien, Austria

About the event

About the Event

This intensive program 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. Through hands-on instruction and guided implementation, participants will learn to master the use of OpenAI APIs for AI agent tasks, implement both standard and Agentic RAG strategies, design robust agentic architectures, and deploy fully functional agentic systems in practical settings.


Prior Knowledge

Participants are expected to have a basic understanding of machine learning concepts and some programming experience, preferably in Python. To ensure a smooth start, approximately six hours of pre-course preparation is recommended. This includes readings on core topics such as AI agent concepts, Retrieval-Augmented Generation (RAG) methodologies, and the OpenAI API documentation. In addition, participants should review and examine sample API integrations and basic agent scripts to become familiar with practical implementation aspects before the course begins.


Detailed Schedule

December 1: Foundations with APIs (8 hours)

Morning: OpenAI APIs Introduction

  • API setup and features

  • Authentication and querying

  • Hands-on workshop: Basic API integration


Afternoon: Deeper API Applications

  • API capabilities for advanced tasks

  • Best practices in agent design using APIs

December 2: Introduction to AI Agents & RAG (8 hours)

December 3, Agentic RAG and Architectures (8 hours)


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Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or Horizon Europe: Marie Skłodowska-Curie Actions. Neither the European Union nor the granting authority can be held responsible for them. This project has received funding from the Horizon Europe research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101119635

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