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.



Intro to Snowflake for Devs, Data Scientists, Data Engineers
This course is part of multiple programs.

Instructor: Snowflake Northstar
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(166 reviews)
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What you'll learn
Create and manipulate Snowflake's core objects, such as virtual warehouses, databases, schemas, tables, and stages.
Use important Snowflake features and objects, such as time travel, cloning, resources monitors, UDFs, stored procedures, and Snowpark DataFrames.
Understand the basics of Snowflake鈥檚 capabilities for data engineering, generative AI, machine learning, and app development.
Skills you'll gain
- Stored Procedure
- SQL
- Data Pipelines
- Data Manipulation
- Generative AI
- Machine Learning
- Database Management
- Cloud Development
- Data Warehousing
- Data Science
- LLM Application
- Role-Based Access Control (RBAC)
- Artificial Intelligence and Machine Learning (AI/ML)
- Data Lakes
- Application Development
- Data Engineering
- Data Storage
- Extract, Transform, Load
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There are 3 modules in this course
After a very brief intro to the course, learners will create a free trial, open a worksheet, and query sample data. They鈥檒l learn about scaling virtual warehouses and create a virtual warehouse to ingest Tasty Bytes data. They鈥檒l learn about stages, databases, schemas, and tables. They鈥檒l manipulate semi-structured data. They鈥檒l also learn about the different Snowflake architectural layers.
What's included
18 videos11 readings8 assignments
Learners will identify a recently introduced 鈥渆rror鈥 in the data and use time travel to correct it. They鈥檒l learn about permanent, transient, and temporary tables, and cloning. They鈥檒l create resource monitors. They鈥檒l create UDFs, a UDTF, and a SQL stored procedure. They鈥檒l learn about role-based access, the VS Code extension, Snowpark DataFrames, and the Snowflake CLI.
What's included
18 videos10 readings9 assignments
Learners will explore four Snowflake workloads: Data Engineering, Generative AI, Machine Learning, and Applications. After reviewing each workload, they鈥檒l see one aspect of that workload in practice: for DE, ingesting streaming data with Snowpipe; for GenAI, using the Snowflake Cortex LLM function 鈥淐omplete鈥; for ML, using Snowpark ML to create an XGBoost model and make predictions about a food truck鈥檚 location; and for apps, running a Streamlit app that shows us Tasty Bytes鈥 daily revenue. They will then learn about the Snowflake Data Cloud.
What's included
21 videos5 readings10 assignments
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Reviewed on Dec 16, 2024
Well-rounded introduction to Snowflake with helpful hands-on experience working with data and objects.
Reviewed on May 19, 2025
Just an excellent course. The instructor's tone makes it very accessible.
Reviewed on Jan 22, 2025
Fantastic introduction with a passionate, if quirky, host. I loved his enthusiasm and insight for Snowflake and hope to see more of his work in future courses.





