Cloud & DevOps Mastery: From Basics to Deployment ( 4 Months Program )
This all-in-one pre-recorded video course is designed to transform beginners and IT professionals into cloud and DevOps experts. Whether you're aiming for a DevOps Engineer, Cloud Architect, or Site Reliability Engineer role, this course will give you hands-on, project-based experience with the most in-demand tools and platforms.
Youβll dive deep into AWS (20+ core services) and Azure cloud platforms, learning how to launch, configure, and manage scalable infrastructure. Then, youβll master key DevOps tools like Git, GitHub, Docker, Kubernetes, Jenkins, Terraform, Maven, Ant, SonarQube, and JIRA to build and automate powerful CI/CD pipelines.Β
100% LiveΒ With Live-recorded HD Video SessionsΒ
Includes Assignments, Quizzes, Mini Projects, and Capstone Projects
Access to cloud lab environments and downloadable resources
Certification of Completion
Basics of Cloud Computing
Cloud Service Models (IaaS, PaaS, SaaS)
Deployment Models (Public, Private, Hybrid)
AWS Overview and Console Walkthrough
EC2 β Launching and managing servers
S3 β Storage management
IAM β Security and roles
VPC β Networking basics
RDS & DynamoDB β Databases
Lambda β Serverless computing
CloudWatch β Monitoring
CloudFormation β Infrastructure as Code
Route 53, ELB, Auto Scaling
SNS, SQS, EBS, EFS, CloudTrail
Cost Management Tools
Hands-on projects and labs
Introduction to Azure Cloud
Azure Portal and CLI
Resource Groups, Azure Storage, VMs
Networking, Security Groups
Azure DevOps Basics
Cost management and compliance
Azure Hands-on labs
What is DevOps?
CI/CD Concepts
Agile & Scrum Methodologies
Git Installation and Setup
Basic Git Commands
Branching, Merging, Conflict Handling
GitHub Integration and Workflows
Real-world collaboration scenarios
Docker Architecture
Creating Dockerfiles
Docker Compose & Networking
Managing Containers
Docker Hub & Docker Registry
Hands-on containerized applications
Kubernetes Architecture
Minikube Setup
Pods, Services, Deployments
ReplicaSets, ConfigMaps, Secrets
Helm Basics
Hands-on Project Deployment in K8s
Jenkins Installation
Pipeline Concepts (Freestyle & Declarative)
Integrating Git, Maven, Docker
Jenkinsfile, Webhooks
Building End-to-End CI/CD Pipeline
IaC Overview
Terraform Syntax & Providers
Managing AWS/Azure Resources via Terraform
Terraform State Management
Hands-on Projects with Git Integration
Introduction to Maven and Ant
Creating & Managing Build Lifecycles
Dependency Management
Integration with Jenkins
Code Quality Concepts
Installing and Configuring SonarQube
Static Code Analysis
Integrating with Jenkins
Introduction to JIRA
Creating and Managing Boards
Sprint Planning, Backlog Management
Integrating with GitHub/Jenkins
Design and deploy a complete CI/CD pipeline
Cloud infrastructure with Terraform
Dockerized microservices on Kubernetes
Code analysis and deployment reporting
By the end of the course, learners will:
Be proficient in deploying and managing cloud applications
Set up complete CI/CD pipelines
Understand containerization and orchestration at scale
Automate infrastructure provisioning with Terraform
Improve code quality using modern tools
Digital certificate issued after completion and final assessment.
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π 12-Month Master Program: Cloud, DevOps, DSA, MLOps & GenAI π Phase 1: Foundations (Month 1 β Month 3) Month 1 β Cloud Basics & DSA Foundations Cloud: Intro to Cloud Computing, IaaS/PaaS/SaaS, AWS/Azure/GCP overview DSA: Complexity Analysis, Arrays, Strings, Recursion Hands-on Project: Deploy a static website on AWS S3 + Basic DSA coding challenges Month 2 β DevOps Fundamentals Version Control: Git, GitHub/GitLab workflows CI/CD Basics: Jenkins, GitHub Actions DSA: Searching & Sorting, Linked Lists Hands-on Project: Set up a CI/CD pipeline for a sample app Month 3 β Cloud Core Services + DSA Expansion Cloud: Compute (EC2, VM), Storage (S3, Blob), Networking (VPC) DSA: Stacks, Queues, Hashing Hands-on Project: Build a 3-tier cloud architecture + DSA problem sets π Phase 2: Intermediate (Month 4 β Month 6) Month 4 β DevOps Intermediate + Cloud IAM Cloud: IAM, Security, Monitoring (CloudWatch, Azure Monitor) DevOps: Docker basics, Containerization DSA: Trees (Binary Trees, BST) Hands-on Project: Dockerize a web app + IAM role-based access project Month 5 β Kubernetes & IaC DevOps: Kubernetes basics (Pods, Deployments, Services) IaC: Terraform, Ansible DSA: Graphs (BFS, DFS, Shortest Path) Hands-on Project: Deploy microservices on Kubernetes Month 6 β Cloud Native & Advanced DevOps Cloud: Serverless (AWS Lambda, Azure Functions, GCP Functions) DevOps: Advanced CI/CD, GitOps (ArgoCD) DSA: Dynamic Programming basics Hands-on Project: End-to-end Serverless app with CI/CD pipeline π Phase 3: Advanced (Month 7 β Month 9) Month 7 β MLOps Foundations MLOps: ML lifecycle, Data pipelines, DVC, MLflow Cloud: Managed AI/ML services (AWS Sagemaker, Azure ML) DSA: Advanced DP, Greedy algorithms Hands-on Project: Train & track ML experiments with MLflow Month 8 β MLOps Deployment Deployment: FastAPI/Flask model serving CI/CD for ML: Kubeflow pipelines Monitoring: Drift detection, logging Hands-on Project: Deploy ML model on Kubernetes with monitoring Month 9 β Generative AI Foundations GenAI: Transformer basics, LLMs overview (GPT, LLaMA, BERT) Prompt Engineering Tools: Hugging Face, LangChain basics Hands-on Project: Build a simple GenAI chatbot with OpenAI API π Phase 4: Specialization (Month 10 β Month 12) Month 10 β GenAI Applications & DSA Advanced GenAI: RAG (Retrieval Augmented Generation), Fine-tuning (LoRA, PEFT) Applications: Chatbots, Image generation, Speech AI DSA: Backtracking, Segment Trees, Bit Manipulation Hands-on Project: Custom knowledge chatbot with LangChain + Vector DB Month 11 β Specialization Track Selection Students choose one specialization: Cloud & DevOps Architect Multi-cloud architecture CI/CD at scale Security, compliance, FinOps MLOps Engineer Advanced pipelines, ML observability Large-scale model deployment GenAI Engineer Fine-tuning LLMs Building multimodal apps (text + image + speech) Hands-on Project: Capstone preparation aligned with specialization Month 12 β Capstone & Career Prep Capstone Projects: Cloud/DevOps β Multi-Cloud E-commerce infra with CI/CD MLOps β End-to-end ML pipeline with monitoring GenAI β AI Copilot app (Chatbot + RAG + API integration) Career Prep: Resume, Interview training, Mock interviews Final Demo Day: Present capstone projects π― Outcome & Certification By end of the program, learners graduate as: Cloud & DevOps Architect (if specialization chosen) MLOps Engineer (if specialization chosen) GenAI Engineer (if specialization chosen) Plus strong foundation in DSA for coding interviews
βοΈ Cloud Computing with ML Ops β Beginner to Advanced (9 Months) Master the future of tech by combining Cloud Computing, DevOps, and Machine Learning Operations (ML Ops) in one powerful program. This 9-month course takes you from foundational cloud skills to advanced ML deployment, including AWS/GCP, Docker, Kubernetes, Python, MLflow, and more. Learn by building real-world projects and get certified with industry-recognized credentials. Ideal for those aiming to become Cloud ML Engineers, ML Ops Specialists, or DevOps Engineers with AI expertise.
π Launch Your Career in Cloud, DevOps & AI with One Power-Packed Course.