Comprehensive Studies of DevOps & Cloud Tools

The Comprehensive Studies of DevOps & Cloud Tools program by Emerging India Analytics delivers hands-on training in DevOps practices, cloud computing, and automation. Covering tools like Linux, Terraform, Puppet, Jenkins, Docker, Kubernetes, and AWS, this program equips learners to build CI/CD pipelines, manage infrastructure as code, and deploy scalable cloud-native applications through real-world projects and guided exercises.

Course Instructor Emerging India Analytics

₹50000.00

Course Overview

In today's fast-evolving IT landscape, mastering DevOps and Cloud Tools is crucial for accelerating software delivery, automating workflows, and managing scalable infrastructure. This 145-hour Comprehensive Studies of DevOps & Cloud Tools program by Emerging India Analytics offers hands-on training designed to equip professionals with practical expertise in Linux, Automation, Configuration Management, Containerization, Cloud Computing, and CI/CD pipelines. Participants will work with industry-standard tools including Terraform for infrastructure as code (IaC), Puppet for automated configuration management, and Jenkins for continuous integration and delivery. Through real-world projects and guided exercises, learners gain the skills to deploy and manage applications efficiently on cloud platforms like AWS and utilize orchestration tools such as Kubernetes for resilient and scalable environments.

Program Overview:

This 145-hour intensive program ,Comprehensive Studies of DevOps & Cloud Tools, equips learners with job-ready skills in modern IT infrastructure and DevOps. It begins with foundational training in Linux and Red Hat system administration, covering command-line operations, user and file management, and basic networking. Learners then dive into configuration management with Ansible and Puppet, gaining hands-on experience automating system setups. The program also covers cloud infrastructure with AWS, focusing on core services like EC2, S3, IAM, and VPC for deploying and managing secure, scalable environments. Containerization and orchestration are taught using Docker and Kubernetes, enabling participants to package and manage applications in production. The curriculum also includes CI/CD pipeline automation with Jenkins and GitLab, along with Infrastructure as Code (IaC) using Terraform. Capstone projects reinforce learning by simulating real-world DevOps scenarios, such as deploying serverless applications, creating automated pipelines, and managing cloud resources, ensuring learners graduate with practical, industry-aligned experience

Program Structure:

30-Hours Pre-Learning Module:  Before you embark on the live academic session, get ready for the Program. You will get a series of online recorded tutorials to understand the basics of Python, Linux, DevOps philosophy, and an overview of cloud computing to prepare for the live sessions.

145-Hours Live Instructor-Led Program Training:  This includes detailed, practical sessions on Linux administration, Red Hat, AWS, Ansible, Docker, Kubernetes, Terraform, Puppet, and CI/CD with Jenkins & GitLab to build automation, orchestration, and deployment skills for real-world DevOps environments.

Access to Recorded Live Videos:  Learning does not stop here. To support better understanding of concepts and skill mastery, recorded videos of live classes will be provided to learners. These videos will be accessible for up to 6 months after course completion.

Specialized Projects & Assignments: To master the skills acquired during the course, learners are required to complete and submit a few projects within one month of course completion. Expert trainers will be available during this period to provide guidance, support, and clarification when needed.

Eligibility:

1. A graduate in any discipline, including Engineering, Science, Mathematics, Statistics, Commerce, Humanities, with a minimum of 50% marks or an equivalent CGPA.
2. Passionate about continuous learning and skill development, with a strong drive to acquire new knowledge in Data Science and Artificial Intelligence.

Certificates:

Schedule of Classes

Course Curriculum

1 Subject