Alessandro Romano is a Senior Data Scientist at Kuehne + Nagel and an accomplished public speaker. With over 7 years of experience in data analysis, he brings deep technical expertise in implementing large language model (LLM) - based solutions across diverse industries.
In this hands-on workshop, you will build an Agentic AI application from scratch and take it all the way to production. Starting from a simple LLM-based workflow, you will progressively introduce tool usage, ReAct-style reasoning, and LangGraph orchestration to create a system capable of making decisions, retrieving information, and taking actions.
You will connect the application to external data sources using RAG, structure and control its behavior through context engineering, and extend its capabilities with MCP and multi-agent patterns. Finally, you will package everything into a Streamlit interface and deploy it to a real cloud service.
By the end of the workshop, you will have a fully working AI knowledge assistant and a clear understanding of how to design and ship production-ready agentic systems in Python.
*Note: These are tentative details and are subject to change.
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