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Building AI Agents with Snowflake

IntermediateSkill Level
Updated 06/2026
Build autonomous Cortex Agents in Snowflake that query structured and unstructured data, then deploy and monitor them.
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SnowflakeArtificial Intelligence
4 hr
24 videos
44 Exercises
2,200 XP
Statement of Accomplishment

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Course Description

Autonomous AI agents are moving beyond chatbots to take real action on enterprise data. In this course, you'll build production-ready Cortex Agents in Snowflake that answer natural-language questions across structured databases and unstructured documents, then learn to evaluate, optimize, and deploy them using orchestration instructions, observability, and the Model Context Protocol.

What you'll learn

  • Differentiate AI agents from traditional AI assistants, and explain how planning, tool calling, and memory let them reason over enterprise data.
  • Recognize enterprise use cases for agentic AI, such as a B2B sales intelligence assistant and a customer service agent for insurance.
  • Determine how to build a working Cortex Agent by creating a semantic view for Cortex Analyst and a Cortex Search service over unstructured documents.
  • Assess how orchestration instructions and observability improve an agent's reliability and guide iteration in production.
  • Define the role of the Model Context Protocol in exposing Snowflake tools to external clients such as Cursor.

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Prerequisites

Building Generative AI Apps to Talk to Your Data
1

Foundations of Agentic AI with Snowflake Cortex

In this chapter, learn how AI agents differ from traditional assistants and how they plan, call tools, and reason over enterprise data through real-world use cases.
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2

Building Your First Cortex Agent

In this chapter, learn how to build a complete B2B sales intelligence agent by creating a semantic view, configuring Cortex Search, and wiring both into a working Cortex Agent.
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3

Advanced Agent Capabilities

In this final chapter, learn how to deploy your agent with Snowflake Intelligence, shape its behavior with orchestration instructions, monitor and iterate on it, and connect it to clients using the Model Context Protocol.
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Building AI Agents with Snowflake
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