Intro to Snowflake for Devs, Data Scientists, Data Engineers

Intro to Snowflake for Devs, Data Scientists, Data Engineers

Taught in English

1,520 already enrolled


Gain insight into a topic and learn the fundamentals

Snowflake Northstar

Instructor: Snowflake Northstar

Beginner level

Recommended experience

10 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace

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’s capabilities for data engineering, generative AI, machine learning, and app development.

Details to know

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May 2024


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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’ll learn about scaling virtual warehouses and create a virtual warehouse to ingest Tasty Bytes data. They’ll learn about stages, databases, schemas, and tables. They’ll manipulate semi-structured data. They’ll also learn about the different Snowflake architectural layers.

What's included

18 videos11 readings8 assignments

Learners will identify a recently introduced “error” in the data and use time travel to correct it. They’ll learn about permanent, transient, and temporary tables, and cloning. They’ll create resource monitors. They’ll create UDFs, a UDTF, and a SQL stored procedure. They’ll 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’ll see one aspect of that workload in practice: for DE, ingesting streaming data with Snowpipe; for GenAI, using the Snowflake Cortex LLM function “Complete”; for ML, using Snowpark ML to create an XGBoost model and make predictions about a food truck’s location; and for apps, running a Streamlit app that shows us Tasty Bytes’ daily revenue. They will then learn about the Snowflake Data Cloud.

What's included

21 videos5 readings10 assignments


Snowflake Northstar
1 Course1,520 learners

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