Mastering RAG: Enhancing AI Applications with Retrieval-Augmented Generation

Pre-registration is REQUIRED.

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Topic: "Mastering RAG: Enhancing AI Applications with Retrieval-Augmented Generation"

In this session, you will:

- Understand RAG: Get a comprehensive overview of how RAG transforms AI's ability to generate reliable, contextually grounded responses by combining external data retrieval with state-of-the-art language models.

- Explore Practical Techniques: Explore different types of RAG flow and practical techniques to enhance RAG performance, including integration with vector databases and fine-tuning methods.

- Address Challenges: Learn about the challenges of RAG implementation based on real cases and highlight the latest trends in the field.

Don't miss this chance to deepen your understanding of RAG and its applications in modern AI. Register now to secure your spot!

Speaker#1: Sheamus McGovern. Founder of ODSC

Sheamus is also a software architect, data engineer, and AI expert. He started his career in finance. Over the last decade, Sheamus has consulted with dozens of companies and startups to build leading-edge data-driven applications in finance, healthcare, eCommerce, and venture capital. He holds degrees from Northeastern University, Boston University, Harvard University, and a CQF in Quantitative Finance.

Speaker#2: Ali Hesham, Data Engineer at Ralabs

Ali is a highly skilled Data Engineer with 4 years of experience in designing and building scalable, reliable data platforms. He excels in crafting robust ETL pipelines and automating data extraction, transformation, and loading (ETL) processes. Proficient in SQL, Python, and core data warehousing tools like BigQuery and Redshift, Ali has deep expertise in cloud platforms including AWS and GCP. In addition to his core engineering skills, Ali has hands-on experience working with Large Language Models (LLMs) and building AI-powered solutions using state-of-the-art techniques. His strong analytical and problem-solving abilities allow him to design effective data models and metadata structures that enable both ad hoc analysis and pre-built reporting, empowering businesses to make data-driven decisions.

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