Build Data Agents

Learn how to build and evaluate a data agent in “Building and Evaluating Data Agents,” a course created in collaboration with Snowflake, and taught by Anupam Datta, AI Research Lead, and Josha Reini, Developer Advocate at Snowflake.

What you’ll do, in detail: 

• Understand what data agents are and how they can be trustworthy when their goal, plan, and actions are properly aligned.
• Build a data agent that plans, performs web searches ,and visualizes or summarizes the results, using a multi-agent workflow implemented in LangGraph. 
• Expand the agent’s capabilities by adding a Cortex sub-agent that retrieves information from structured and unstructured data stored in Snowflake. 
• Add tracing to the agent’s workflow to log the steps it takes to answer a query.
• Evaluate the context relevance of the retrieved results, the groundedness of the final answer, and its relevance to the user’s query.
• Measure the alignment of the agent’s goal, plan, and actions (GPA) by computing metrics such as plan quality, plan adherence, logical consistency,y and execution efficiency. 
• Improve the agent’s performance by adding inline evaluations and updating the agent’s prompt..

By the end, you’ll know how to build, trace, and evaluate a multi-agent workflow that plans tasks, pulls context from structured and unstructured data, performs web searches, and summarizes or visualizes the final results.