Snowflake Generative AI

Snowflake via Coursera Professional Certificate

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Provider

Coursera Professional Certificate
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Duration & workload

4 weeks, 10 hours a week

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Overview

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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.

Syllabus

Course 1: Intro to Snowflake for Devs, Data Scientists, Data Engineers
Course 2: Introduction to Generative AI with Snowflake
Course 3: Building Generative AI Apps to Talk to Your Data
Course 4: Building AI Agents with Snowflake

Courses

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10 hours 37 minutes
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This course introduces learners to Snowflake as a platform for building applications, data pipelines, and AI models and workflows. It takes them from zero Snowflake knowledge all the way to creating user-defined functions, using a Snowflake Cortex LLM function, editing a Streamlit app, and more. The course unfolds in three parts: First, participants learn to use Snowflake’s core objects such as virtual warehouses, stages, and databases. Then they learn about slightly more advanced objects and features such as time travel, cloning, user-defined functions, and stored procedures. Finally, they’re introduced to Snowflake’s capabilities for data engineering, generative AI, machine learning, and app development. Learners come away equipped to start building with Snowflake and to continue their Snowflake learning journeys. This course is a prerequisite for upcoming Snowflake courses on data engineering, AI, and apps.
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4 hours 41 minutes
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This course introduces learners to generative AI and how to implement common AI use cases using Snowflake. The course starts with an introduction of important concepts, the setup of the learner environment, and the building of a simple application. It’s followed by learning how to use the Cortex LLM functions to accomplish many common AI tasks, and ends with learning how to fine-tune foundation models to perform specific tasks. This course is for anyone looking to skill up on AI, but is particularly suited for data scientists, ML/AI engineers and data analytics professionals. To be successful in this course, you should have a background in Python, GenAI, and LLMs.
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5 hours 57 minutes
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In this course, you’ll learn how to build conversational AI applications that let users interact with their data, whether structured in tables or unstructured in documents, using natural language. Designed as the next step after our Intro to GenAI course, this course focuses on building practical applications with Snowflake Cortex, including Cortex Search for unstructured data and Cortex Analyst for structured data. You'll gain the skills to connect these applications to real data sources, build robust backends, and deliver user-friendly interfaces for GenAI apps using Streamlit. By the end, you’ll know how to design, build, and deploy end-to-end GenAI apps that democratize access to the insights previously locked away in data. This course is built for developers, data scientists, and ML engineers looking to bring natural language interfaces into their organizations.
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4 hours 57 minutes
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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.