Throughout this course, you'll explore virtualization, containerization, and Kubernetes, mastering the very tools that power data engineering in the industry. Each week presents a new set of tools and platforms that are indispensable in data engineering. From mastering Docker and Kubernetes to exploring advanced topics such as AI-driven coding with GitHub Copilot, efficient container image management with Azure and Amazon Elastic Container Registries, and Site Reliability Engineering (SRE) practices, you'll go beyond the basics and acquire the expertise needed to thrive in the dynamic and data-driven landscape of advanced data engineering. Whether you're a current student looking to expand your skills or a working professional aiming to take your expertise to the next level, this course is tailored to equip you with the advanced knowledge and hands-on experience necessary for success.

Virtualization, Docker, and Kubernetes for Data Engineering
本课程是 Applied Python Data Engineering 专项课程 的一部分



位教师:Noah Gift
访问权限由 New York State Department of Labor 提供
6,440 人已注册
您将学到什么
Master virtualization, containerization, and Docker, including Dockerfile creation and multi-container orchestration with Compose and Airflow.
Develop expertise in Kubernetes core concepts, cluster architecture, and deployment using cloud environments, GitHub Codespaces, and AI-driven tools.
Navigate data scenarios mastering containerization, deploying apps, and addressing production issues with cloud orchestration and SRE practices.
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要了解的详细信息

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38 项作业
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该课程共有4个模块
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学生评论
- 5 stars
51.02%
- 4 stars
12.24%
- 3 stars
12.24%
- 2 stars
10.20%
- 1 star
14.28%
显示 3/49 个
已于 Feb 18, 2024审阅
It was great but the last module of week 4 felt isolated from the rest of the course.
已于 Mar 19, 2025审阅
For the first time I really understood what "virtualization" is and how things sort of expand for larger and larger units. Really solid stuff on CI/CD stuff also.
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