The DevOps Engineer Masterclass teaches you how to build automated pipelines, manage containerized infrastructure, and streamline deployment workflows. Through 20+ hands-on sessions, you'll use industry-standard tools like Docker, Kubernetes, Jenkins, and Terraform to deliver applications faster and more reliably.
About Course
This course walks you through the DevOps lifecycle: from version control and continuous integration to configuration management and infrastructure provisioning. You’ll learn to containerize applications, deploy them on Kubernetes, and automate processes using Jenkins and Terraform. Whether you're new to DevOps or upskilling, this course prepares you to manage modern development pipelines.
No, the course starts with Linux and scripting basics—no prior experience needed.
Yes, you'll learn Docker and Kubernetes for containerization and deployment.
Absolutely—AWS, Azure, and other cloud platforms are covered.
Yes, all tools are installable on a standard laptop or accessible via the cloud.
Yes, you'll create end-to-end CI/CD pipelines using tools like Jenkins, Git, and Docker.
What Will You Learn?
- Version Control with Git & GitHub – Collaborate with teams and manage code using best practices in Git workflows.
- CI/CD with Jenkins – Build and automate continuous integration pipelines with Jenkins using real-world job configuration.
- Docker for Containerization – Containerize applications for consistency across development, staging, and production.
- Kubernetes Orchestration – Deploy, scale, and manage containerized applications on Kubernetes clusters.
- Infrastructure as Code (IaC) – Provision and manage infrastructure with Terraform and Ansible.
- Cloud Integration (AWS/Azure) – Host and scale DevOps workloads on cloud providers with security and monitoring.
- Monitoring and Logging – Use Prometheus, Grafana, and ELK Stack to visualize system performance and logs.
Audience
Perfect for developers, system administrators, QA engineers, or IT professionals seeking a DevOps career path. Also ideal for freshers aiming to build a DevOps portfolio from scratch.
Course Content:
Understanding the role of a data scientist
Key concepts in data science
Overview of the data science process
Python programming basics
Data manipulation with pandas
Data visualization with matplotlib and seaborn
