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Snowflake Northstar

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.

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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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What's inside

Syllabus

Snowflake’s Core Objects and Architecture
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.
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Snowflake Feature Overview
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.
Overview of Builder Workloads: Data Engineering, AI / ML, Apps
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.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches learners how to use Snowflake features, such as virtual warehouses and databases, to build applications
Develops skills in using Snowflake's advanced capabilities, such as user-defined functions and stored procedures
Provides hands-on labs and interactive materials, which allows learners to apply their knowledge and skills
Taught by Snowflake Northstar, who are recognized for their expertise in the Snowflake platform
Covers core Snowflake objects and architecture, as well as more advanced features such as time travel and cloning
Prerequisites are necessary for this course

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Intro to Snowflake for Devs, Data Scientists, Data Engineers with these activities:
Organize Previous Knowledge
Organize notes and assignments from previous courses to refresh your knowledge of data management and analysis.
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  • Gather materials from previous courses
  • Organize materials by topic
  • Review your notes and assignments
Practice SQL Queries
Sharpen your SQL skills by practicing data querying and analysis tasks.
Browse courses on SQL
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  • Find practice problems or exercises
  • Practice writing and executing SQL queries
  • Review your results and identify areas for improvement
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Career center

Learners who complete Intro to Snowflake for Devs, Data Scientists, Data Engineers will develop knowledge and skills that may be useful to these careers:

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