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Generative AI Essentials with Snowflake

IntermediateSkill Level
Updated 06/2026
Build generative AI apps on Snowflake with Cortex LLM functions, prompt engineering, and fine-tuning.
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SnowflakeArtificial Intelligence
3 hr
21 videos
47 Exercises
2,350 XP
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Course Description

This course introduces learners to generative AI and how to implement common AI use cases using Snowflake. The course starts with an introduction to 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.

What you'll learn

  • Define core generative AI concepts and build a simple Snowflake app that loads unstructured data and summarizes it with Cortex COMPLETE.
  • Determine when to use the Cortex COMPLETE function with prompt engineering, and select an appropriate foundation model and parameters for a use case.
  • Differentiate the task-specific Cortex functions - translation, sentiment analysis, summarization, and classification - and when each one fits a task.

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Prerequisites

There are no prerequisites for this course
1

Introduction to GenAI on Snowflake

Get introduced to the core generative AI concepts and the Snowflake capabilities that bring them to life. You'll set up your Snowflake environment, work in Snowflake Notebooks, and build a simple AI app that loads unstructured call-transcript data from an S3 bucket, prompts a foundation model to summarize it as JSON, and surfaces the results in a Streamlit UI.
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2

Snowflake Cortex's LLM-Based Functions

Dive into Snowflake Cortex's LLM-based functions to accomplish a wide range of AI tasks. You'll implement common use cases like summarization, translation, sentiment analysis, and text classification with task-specific functions, run open-ended prompts through the Cortex COMPLETE function with Llama, Mistral, and Anthropic models, choose the right LLM for the job, and use helper functions to estimate token count and cost before you spend it.
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Generative AI Essentials with Snowflake
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