Title: Virtualization, Docker, and Kubernetes for Data Engineering
Location: US
Company: Pragmatic AI Labs
About this course:
Dive into the world of virtualization, containerization, and orchestration for data engineering:
Understand virtualization fundamentals and work with virtual machines
Explore Docker containers and build scalable microservices
Orchestrate containers using Kubernetes and cloud platforms
Utilize cloud development environments like GitHub Codespaces
Learn production best practices, including monitoring, testing, and CI/CD
Gain practical experience with industry-standard tools and techniques. Develop the skills to build, deploy, and manage containerized data solutions at scale. Whether you're a student or data professional, level up your data engineering capabilities.
Virtualization concepts and virtual machines
Docker containers and microservices
Kubernetes architecture and deployments
Cloud development with GitHub Codespaces
Container registries for Kubernetes
Cloud-based Kubernetes solutions
Production monitoring, testing, and CI/CD
Master virtualization, Docker, and Kubernetes for data engineering. Gain hands-on experience with cloud development environments, container orchestration, and production best practices.
Duration: 4 weeks
Curriculum:
- Module 1: Virtualization Theory and Concepts (6 hours to complete)
- Module 2: Using Docker (5 hours to complete)
- Module 3: Kubernetes: Container Orchestration in Action (6 hours to complete)
- Module 4: Building Kubernetes Solutions (9 hours to complete)
Show interest and get access to the course
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