This course is for AI engineers, application developers, data engineers, data analysts, other data professionals, and students who want to build autonomous AI agents that work with enterprise data. Whether you're looking to move beyond basic chatbots, create intelligent systems that can query both structured databases and unstructured documents, or integrate AI capabilities into existing business workflows, this course provides the hands-on foundation you need.
By the end of this course, you will be able to:
- Distinguish between AI assistants and AI agents, and identify when autonomous agent capabilities are the right solution for your use case
- Build Cortex Analyst and Cortex Search that enable agents to query structured metrics and search unstructured content using natural language
- Configure and deploy Cortex Agents that autonomously plan tasks, select appropriate tools, and synthesize insights from multiple data sources
- Write effective orchestration instructions that guide agent behavior and optimize response quality
- Evaluate agent reliability using observability features and implement improvements based on performance metrics
- Connect agents to external applications using Model Context Protocol for broader integration
To be successful in this course, you should have basic familiarity with SQL and understand how data is organized in databases. Prior experience with AI or machine learning is helpful but not required, as the course covers foundational agent concepts before moving into implementation. This is a hands-on course where you'll build alongside the instructor, so you'll use a free Snowflake trial account.
In this module, you'll learn what makes AI agents different from traditional AI assistants and why this distinction matters for enterprise applications. You'll explore how agents autonomously plan, execute, and reflect on complex tasks rather than simply responding to direct queries. The module covers Snowflake's agentic AI architecture including Cortex Agents, Cortex Analyst, and Cortex Search, and how these components work together. You'll examine real-world use cases in B2B sales intelligence and customer service to understand when agent capabilities are the right solution for business problems.
涵盖的内容
8个视频1篇阅读材料1个作业
显示有关单元内容的信息
8个视频•总计39分钟
Welcome to Building Agentic AI Applications with Snowflake Cortex•4分钟
Understanding AI Agents vs. AI Assistants•4分钟
How Agents Work - Planning & Tool Calling•6分钟
How Agents Work - Memory & RAG Integration•2分钟
Enterprise Use Case - B2B Sales Intelligence Assistant•6分钟
Enterprise Use Case - Customer Service Agent for Insurance•8分钟
Agent Demonstration•6分钟
Module 1 Summary and What's Next•3分钟
1篇阅读材料•总计10分钟
Why Agents Behave the Way They Do•10分钟
1个作业•总计30分钟
Module 1 Assessment (Knowledge Check)•30分钟
Building Your First Cortex Agent
第 2 单元•小时 后完成
单元详情
In this module, you'll build a complete B2B sales intelligence agent from scratch using Snowflake's visual interfaces. You'll create a semantic view for Cortex Analyst that enables natural language queries over structured sales metrics, configure Cortex Search for unstructured conversation transcripts, and connect both as tools to an agent. You'll write orchestration instructions that guide agent behavior and test your agent with questions that require structured data, unstructured data, and both combined. By the end, you'll have a working agent that autonomously decides which tools to use based on the question asked.
涵盖的内容
7个视频2篇阅读材料1个作业
显示有关单元内容的信息
7个视频•总计37分钟
From Exploration to Building•3分钟
Reviewing the Tables•3分钟
Creating Your Semantic View•9分钟
Creating Your Search Service•5分钟
Creating Your Agent•8分钟
Optimizing Agent Performance•6分钟
What You've Built•3分钟
2篇阅读材料•总计20分钟
Course Setup•10分钟
[IMPORTANT] Have Questions? Join the Q+A Forum for this course•10分钟
1个作业•总计30分钟
Module 2 Assessment (Knowledge Check)•30分钟
Advanced Agent Capabilities
第 3 单元•小时 后完成
单元详情
In this module, you'll expand your agent skills with advanced capabilities for production use. You'll learn how agents handle complex multi-step scenarios through task decomposition. The module covers response optimization techniques including instruction refinement for orchestration and response format. You'll learn how to evaluate agent reliability using Snowflake's observability features. Finally, you'll configure Model Context Protocol to connect your agents with external applications, extending their reach beyond Snowflake.
涵盖的内容
9个视频4篇阅读材料1个作业
显示有关单元内容的信息
9个视频•总计61分钟
Your Agent in Snowflake Intelligence•7分钟
Create Logic Flow using Orchestration Instructions Part 1•6分钟
Create Logic Flow using Orchestration Instructions Part 2•7分钟
A single, global platform that powers the Data Cloud. Snowflake is uniquely designed to connect businesses globally, across any type or scale of data and many different workloads, and unlock seamless data collaboration.
What is the difference between an AI agent and a chatbot?
AI agents are autonomous systems that can plan, reason, and take multi-step actions to accomplish goals. Unlike traditional chatbots that simply respond to direct queries, AI agents can break down complex problems, decide which tools to use, and synthesize information from multiple data sources. This course teaches you to build AI agents using Snowflake Cortex that combine structured database queries with unstructured document search.
What is Snowflake Cortex Agents?
Snowflake Cortex Agents is a platform for building autonomous AI agents that work with enterprise data. It includes Cortex Analyst for querying structured data using natural language, Cortex Search for finding information in unstructured documents, and orchestration capabilities that let agents autonomously decide which tools to use. This course teaches you to configure and deploy Cortex Agents through hands-on exercises.
What is Model Context Protocol (MCP)?
Model Context Protocol is an open standard that allows AI agents to connect with external applications and data sources. MCP enables your Snowflake agents to integrate with tools like Claude Desktop, Cursor, and other AI applications. This course covers how to configure Snowflake's managed MCP servers to extend your agents beyond the Snowflake environment.
What business problems can AI agents solve?
AI agents excel at tasks requiring information from multiple sources. Examples include sales intelligence that combines conversation transcripts with deal metrics, customer service that searches policies while accessing account data, and financial analysis that synthesizes reports with structured performance data. This course uses a B2B sales intelligence scenario to teach agent development with real-world applicability.
What is a semantic view in Snowflake Cortex Analyst?
A semantic view is a business context layer that maps natural language terms to database tables and calculations. It allows AI agents to understand questions like "What's our win rate?" without users writing SQL. Semantic views define dimensions for slicing data, measures for calculations, and synonyms for flexible language interpretation. This course teaches you to build semantic views through Snowflake's visual interface.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Certificate?
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.