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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/snowflake-intro-app-developers-data-scientists-data-engineers
课程评论：没有评论
课程名称：开发者、数据科学家和数据工程师的Snowflake入门 概述：该课程向学习者介绍Snowflake作为构建应用程序、数据管道和AI模型及工作流程的平台。从零基础开始，学习者将掌握创建用户定义函数、使用Snowflake Cortex LLM功能、编辑Streamlit应用程序等技能。 课程分为三个部分： 第一部分：Snowflake的核心对象与架构 学习者将快速了解课程内容，创建免费试用帐户，打开工作表并查询示例数据。他们将学习如何扩展虚拟仓库，并创建虚拟仓库来获取Tasty Bytes数据，同时了解阶段、数据库、模式和表。学习者将处理半结构化数据，并了解Snowflake的不同架构层次。 第二部分：Snowflake功能概述 学习者将识别数据中的最近引入的“错误”，并利用时间旅行功能进行修正。他们将学习永久、临时和过渡表及克隆的用法，创建资源监视器，用户定义函数（UDF）、用户定义表函数（UDTF）和SQL存储过程的创建。此外，还将学习基于角色的访问控制、VS Code扩展、Snowpark数据框以及Snowflake CLI。 第三部分：构建工作负载概述：数据工程、AI/ML、应用程序 学习者将探索四种Snowflake工作负载：数据工程、生成式AI、机器学习和应用程序。每种工作负载将有实际案例展示：在数据工程中，使用Snowpipe摄取流数据；在生成式AI中，利用Snowflake Cortex LLM功能“Complete”；在机器学习中，使用Snowpark ML创建XGBoost模型并预测食品卡车的位置；在应用程序中，运行一个展示Tasty Bytes每日收入的Streamlit应用。学习者最终将了解Snowflake数据云。
Name:Snowflake’s Core Objects and Architecture
Description: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.
Name:Snowflake Feature Overview
Description: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.
Name:Overview of Builder Workloads: Data Engineering, AI / ML, Apps
Description: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.
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 f
