AI agents represent a fundamental shift from directed assistants to autonomous systems that can plan, execute, and adapt independently. Organizations need professionals who can build intelligent systems that work across structured databases and unstructured documents like contracts, emails, and conversation transcripts.
This hands-on course teaches you to build production-ready AI agents using Snowflake Cortex. You will learn the core differences between AI assistants and autonomous agents, then build your own sales intelligence agent that combines deal metrics with customer conversation analysis.
Skills you will gain include configuring semantic views for natural language database queries, building hybrid search services for unstructured text, writing effective orchestration instructions, evaluating agent reliability, and integrating agents with external applications using Model Context Protocol.
The course emphasizes learning by doing. You will work with realistic B2B sales data and insurance scenarios, building agents that answer complex business questions by autonomously selecting the right tools and synthesizing insights from multiple data sources.
By completion, you will understand how to design agent architectures, implement multi-step workflows, optimize agent responses, and deploy agents through both programmatic APIs and visual interfaces.
This course prepares you for roles in AI application development and data engineering with AI capabilities.
Applied Learning Project
Throughout this course, you will build two complete AI agents that solve real business problems.
In the first project, you will create a B2B sales intelligence agent. Using sample sales data including deal metrics and customer conversation transcripts, you will configure semantic views, build a hybrid search service, and connect both tools to an agent that autonomously answers complex sales questions. Your agent will analyze win rates, search transcripts for customer concerns, and synthesize insights from both data sources.
In the second project, you will build an insurance customer service agent with advanced capabilities. You will implement multi-step workflows for claims analysis, configure response optimization, and integrate your agent with external applications using Model Context Protocol.
Both projects use realistic datasets that mirror enterprise scenarios. You will have working agents you can showcaseyour ability to design, build, and deploy Agentic AI systems.
