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所在平台: Udemy |
课程主页: https://www.udemy.com/course/aws-data-engineering-labs/
课程评论：没有评论
课程名称：AWS 数据工程实验室 课程概述：本课程是一个实操导向的培训，旨在帮助熟悉 AWS 的个人提升他们在数据工程方面的技能。学员们需要对 Python、SQL 及数据库概念有基本了解，不过即使是数据工程领域的新手也能轻松跟进学习。课程内容以实践为主，理论知识相对较少，重点在于 AWS 上的数据工程实践。参与者将通过一系列实验获得实践经验，涵盖 AWS 的核心服务，如 Glue、Lambda、Kinesis、S3、Redshift、EventBridge 等。尽管实验提供了实用的练习，参与者仍然被鼓励参考 AWS 文档，以全面理解相关概念。此外，本课程还将为学员准备数据工程认证（DEA-C01）提供实用经验。 课程内容包括： - 在 Glue 创建数据目录并在 Athena 中查看数据 - 使用 Glue 运行 ETL 作业 - 利用 EventBridge 触发 S3 上传事件的 SNS 通知 - 使用 Step Functions 状态机协调 Lambda 函数 - 使用 AWS Glue、Lambda、EventBridge 和 Step Functions 进行 ETL 工作流编排 - 使用 AWS CLI 从 Kinesis 数据流存取和检索数据 - Kinesis 数据流的 Python Boto3 生产者与消费者 - 使用 AWS Lambda 将模拟天气数据从 Kinesis 流写入 S3 - 在 EC2 上使用 Amazon EMR 运行 Spark 转换作业 - 在 S3 数据上创建数据仓库使用 Amazon Redshift - 理解 PySpark 基础知识与 Databricks - 在 AWS 上设置 Databricks 课程中还会提供 DEA-C01 考试的一些问题和解答。 先决条件：对 AWS 有基本理解，具备基本的 Python、SQL、Spark 和数据库概念知识。注意：即使您是 AWS 和数据工程的初学者，也可以顺利学习本课程。
This hands-on course is designed for individuals familiar with AWS to enhance their skills in data engineering. Students should have a basic understanding of Python, SQL, and database concepts. However, even beginners to data engineering can follow along and learn. The course is minimal on theory, focusing instead on practical aspects of data engineering on AWS. Participants will gain practical experience through a series of labs covering essential AWS services such as Glue, Lambda, Kinesis, S3, Redshift, EventBridge, and more. While the labs provide practical exercises, participants are encouraged to refer to AWS documentation for a full understanding of concepts. This course will also give you practical experience to aid in your preparation for the Data Engineering certification (DEA-C01). AWS Data Engineering Labs:Creating a data catalog in Glue and viewing data in AthenaRunning an ETL job using GlueTriggering SNS Notification for S3 Upload Event using EventBridgeOrchestrating Lambda functions with Step Functions State MachineETL Workflow Orchestration with AWS Glue Lambda EventBridge Step FunctionsStoring and Retrieving Data from a Kinesis Data Stream Using AWS CLIKinesis Data Stream Python Boto3 Producer & ConsumerWriting simulated weather data from a Kinesis Stream to S3 with AWS LambdaRunning Spark transformation jobs using Amazon EMR on EC2Creating a Data Warehouse on S3 data using Amazon RedshiftUnderstanding PySpark Basics with DatabricksSetting up Databricks on AWSAlso you will find some questions and answers for the DEA-C01 exam.Prerequisites:Basic understanding of AWSBasic knowledge of Python, SQL, Spark and database conceptsNote: Even if you are a beginner to AWS and Data Engineering, you can still follow and learn from this course.
