Build an AI Agent for Data Analysis with LLM Reasoning

This 15-minute tutorial from Nvidia demonstrates how to build an intelligent data analysis agent that combines advanced LLM reasoning with interactive data visualization. Explore a modular agent architecture featuring specialized components for data insights, code generation, execution, and reasoning. Leverage NVIDIA Llama 3.1 Nemotron Ultra, a powerful 253-billion-parameter model, to create a Streamlit application that allows users to upload CSV files and analyze data using natural language queries. Learn how the system automatically generates Python code, creates dynamic visualizations, and provides transparent step-by-step reasoning. The tutorial covers the importance of reasoning in AI agents, NVIDIA's model family (Nano, Super, and Ultra), technical implementation details, and includes a live demonstration using the Titanic dataset. Access the complete code on GitHub and explore additional resources including datasets, technical reports, and the NeMo Framework to start building your own data analysis agent with advanced reasoning capabilities.