Developing AI Agents with Snowflake

Organizations are sitting on massive amounts of enterprise data, but turning that data into automated, intelligent action requires more than standard queries. This course introduces you to the fundamentals of building autonomous AI agents directly where your data lives. You will transition from writing basic SQL queries to designing data-aware AI agents that can reason, search, and interact with your databases securely. Through clear, written explanations, you will learn how to leverage built-in cloud intelligence capabilities to build applications that respond to natural language and execute complex workflows. What you'll learn: - Understand the foundational architecture of AI agents and large language model integrations. - Configure secure vector search and retrieval-augmented generation (RAG) workflows. - Apply modern prompt engineering techniques to guide agent decision-making. - Build interactive conversational interfaces using Streamlit for rapid prototyping. - Implement governance and security best practices for AI models handling sensitive data. - Design agentic workflows that connect language models to structured SQL databases. Starting with core definitions and architectural basics, the text-only curriculum guides you step-by-step through setting up data pipelines, connecting language models, and deploying functional agent interfaces. This course is designed for data professionals, developers, and analysts looking to enter the AI engineering space. A basic understanding of SQL and Python is helpful, but no prior machine learning or AI experience is required. Start reading today to unlock the power of agentic AI within your data platform.