About This Program
Master end-to-end CI/CD, containerization, and cloud deployment with AWS/Azure, Kubernetes, Docker, Terraform, and DevSecOps. Become job-ready in 3 months with a live capstone project and mentorship.
Course Overview
This intensive 3-month program transforms beginners into job-ready DevOps Engineers. Learn to design, automate, and monitor CI/CD pipelines using Jenkins/GitHub Actions, Docker, Kubernetes, and Terraform for cloud deployment. The program emphasizes the DevOps mindset, security integration, and a capstone project simulating real-world environments.
What You Will Learn
Hands-on Projects
Apply your learning through real-world projects that build your portfolio
Unique method to make you professionally rich
Progress through our comprehensive program which makes qualified professional to earn their awards
Bronze Award
Begin your journey with foundational skills and basic certification.
Course Curriculum
Technologies You Will Learn
Master the most in-demand tools and technologies for data analytics
CI/CD: Jenkins, GitHub Actions
Containerization: Docker, Docker Compose
Orchestration: Kubernetes, Helm
Infrastructure as Code: Terraform
Cloud Platforms: AWS, Azure
Monitoring & Logging: Prometheus, Grafana, ELK/EFK
Scripting & Automation: Bash, Python
Version Control: Git, GitHub
Other: Linux, Unit & Integration testing frameworks
What Our Students Say
Hear from our students who have transformed their careers
Why Choose Edjamon?
Discover the difference between Edjamon and traditional platforms
| Features & Criteria | EdJAMON | Others |
|---|---|---|
Project Scope | End-to-end multi-service CI/CD and cloud deployment | Limited projects; partial deployment or theoretical exercises |
Learning Format | Live classes + Weekly code reviews + Hands-on labs | Mostly self-paced recordings |
CI/CD & DevOps | Full automated CI/CD pipeline implementation | Limited pipeline exposure |
Security Focus | DevSecOps integration with pipeline security | Weak or no DevSecOps coverage |
Monitoring & Logging | Prometheus, Grafana, ELK/EFK with actionable dashboards | Basic monitoring without actionable dashboards |
Cloud Platforms | AWS and Azure cloud deployment with Terraform | Single cloud or theoretical exposure |
Placement Support | Resume prep, mock interviews, hiring connections | Minimal or no placement support |
Job Roles After Program
Explore exciting career opportunities
DevOps Engineer
CI/CD Engineer
Cloud & Infrastructure Engineer
Site Reliability Engineer (SRE)
Automation / Release Engineer
Kubernetes / Docker Specialist
Become the top 1% in your domain
Explore our specialized programs to accelerate your career
Resources & References
Access curated external resources to deepen your understanding
LLMs & Generative AI
Official guide for GPT models and API usage
Pre-trained models, datasets, and community resources
Open-source LLaMA models and implementation guides
Claude AI research papers and documentation
RAG & Framework Docs
Complete guide to building LLM applications
Data indexing framework for LLM applications
Step-by-step RAG implementation
Efficient open-source LLM models
Vector Databases
Cloud-native vector database for AI applications
Facebook's efficient similarity search library
Open-source ML-first vector database
Open-source embeddings database
Best Practices & Learning
OpenAI's official prompt engineering best practices
Academic foundation for RAG architectures
Real-world RAG implementation patterns
Security and ethical considerations for AI apps
Deployment & DevOps
Containerization and deployment guide
CI/CD automation and workflow automation
Build data apps with simple Python scripts
Cloud deployment and infrastructure setup
Python & Development
Complete Python language reference
Modern Python web framework for APIs
Numerical computing with Python
Data manipulation and analysis library
Frequently Asked Questions
Find answers to common questions