D24
GrowthIntermediate6 weeks
Cloud Computing
Get hands-on with cloud infrastructure, deployment, and scaling on modern platforms like AWS and Azure.
What you'll learn
Core cloud concepts across AWS, Azure, and GCP
Deploying and scaling applications in the cloud
CI/CD pipelines for automated deployments
Monitoring, cost management, and security basics
Course details
Duration
6 weeks
Best for
Developers ready to deploy and scale real applications
On completion
Verified certificate & placement assistance
Compare enrollment modes
| Mode | Price | What you get |
|---|---|---|
| Live Class | ₹4,999 | Instructor-led live cohort with doubt-clearing sessions — includes both the course and internship certificates. |
| Recorded Batch | ₹2,999 | Full recordings of a completed live batch — includes both the course and internship certificates. |
| Internship | ₹2,499 | Work on 4 real projects with our team and earn an internship certificate (course certificate not included). |
| Self-Paced | ₹1,999 | Learn anytime with the full recorded curriculum and community access. |
Choose how you learn
Course Curriculum
A module-by-module breakdown of what you'll cover in Cloud Computing.
01
Getting Started & Environment Setup
Week 1- Setting up free-tier AWS and Azure accounts
- Installing the Terraform CLI
- Installing Docker Desktop and kubectl
- Verifying access with a basic CLI command against each cloud
02
Linux, Networking & Cloud Fundamentals
Week 2- Linux command line, shell scripting, and file permissions
- TCP/IP, DNS, and SSH-based remote administration
- Core AWS and Azure services: compute, storage, and networking
- IAM roles, security groups, and least-privilege access design
03
Infrastructure as Code with Terraform
Week 3- HCL syntax, providers, and reusable modules
- Remote state management and backends
- Variables, outputs, and workspaces
- Team workflows with Terraform Cloud/CLI and pull-request reviews
04
Containers & Kubernetes
Week 4- Writing efficient multi-stage Dockerfiles and managing registries
- Pods, Deployments, Services, ConfigMaps, and Secrets
- Packaging applications with Helm charts
- Deploying to local and managed Kubernetes clusters
05
CI/CD Pipeline Engineering
Week 4- Pipeline-as-code and build/test/deploy stages
- Artifact and container image versioning
- Promoting releases across dev, staging, and production
- Managing secrets safely inside pipelines
06
Site Reliability & Observability
Week 5- Horizontal and vertical autoscaling strategies
- Metrics and dashboards with Prometheus and Grafana
- Defining SLIs/SLOs and writing incident runbooks
- Service mesh fundamentals
07
AI-Assisted Operations, Cost & Security
Week 6- Using AI coding assistants to draft and review infrastructure code
- Anomaly detection and cost/rightsizing optimization across clouds
- Security scanning: SAST/DAST, container image, and secrets scanning
- Compliance baselines and vulnerability triage workflows
Tools & Technologies
Hands-on practice with the same tools used by working professionals.
LinLinux
AWSAWS & Azure
TFTerraform
DocDocker & Kubernetes
GHGitHub Actions
ProPrometheus & Grafana
SnySnyk / Checkov
Hands-on Projects
This is project-based learning — you'll build real, portfolio-ready work as you go, not just watch lectures.
Multi-tier web app on AWS & Azure — provision a load-balanced web, app, and database tier from one Terraform codebase across two clouds
Kubernetes microservices deployment — containerize a multi-service app and deploy it via Helm with rolling updates
CI/CD pipeline with automated testing — build a pipeline that lints, tests, builds, and deploys to staging on every merge
Observability stack with alerting — instrument a service with Prometheus/Grafana dashboards and page on SLO breach
DevSecOps pipeline with security gates — add SAST, dependency, and container scanning that blocks merges on critical findings
Every course includes a guided internship on top of your project work — so you graduate with real experience, not just a certificate.
Communication & Soft Skills
Built into every course, alongside the technical curriculum.
Communication Skills
Practice explaining technical work clearly to teammates, managers, and clients.
Practical AI Skills
Hands-on training in using AI tools well — prompting, everyday workflows, and where AI actually helps versus where it doesn't.
Teamwork & Collaboration
Work in small project teams using real workflows like stand-ups and code reviews.
Problem Solving
Build the habit of breaking down ambiguous problems into clear, solvable steps.
Time Management
Learn to plan, prioritize, and deliver project work against realistic deadlines.
Presentation Skills
Present your project work and results with confidence, as you would to a client.
Resume & Profile Building
Build a strong resume, LinkedIn profile, and project portfolio that recruiters notice.
Interview Preparation
Mock interviews and portfolio reviews to get you ready for real job applications.
Student Reviews
“Practical, hands-on labs made cloud concepts stick in a way tutorials never did.”
Balaji Iyer
DevOps Engineer
“The CI/CD module alone leveled up how our whole team ships code.”
Kavya Menon
Backend Developer
Frequently Asked Questions
What will I learn in the Cloud Computing course?
You'll learn: Core cloud concepts across AWS, Azure, and GCP; Deploying and scaling applications in the cloud; CI/CD pipelines for automated deployments; Monitoring, cost management, and security basics.
What tools and technologies does the Cloud Computing course cover?
This course covers: Linux, AWS & Azure, Terraform, Docker & Kubernetes, GitHub Actions, Prometheus & Grafana, Snyk / Checkov.
Is the Cloud Computing course beginner-friendly?
This is a intermediate-level course. It still starts with a "Getting Started & Environment Setup" module covering tool installation, but assumes some prior familiarity with the subject.
How long does the Cloud Computing course take to complete?
The course is designed to be completed in approximately 6 weeks, depending on your pace.
What enrollment options are available for Cloud Computing?
Live Class (₹4,999) — Instructor-led live cohort with doubt-clearing sessions — includes both the course and internship certificates. Recorded Batch (₹2,999) — Full recordings of a completed live batch — includes both the course and internship certificates. Internship (₹2,499) — Work on 4 real projects with our team and earn an internship certificate (course certificate not included). Self-Paced (₹1,999) — Learn anytime with the full recorded curriculum and community access.
Is there an internship option for Cloud Computing?
Yes — enrolling in the Internship track (or the Live/Recorded tracks, which include it) means working through 4 real projects with our team and earning a separate Internship Certificate, in addition to the course completion certificate for Live/Recorded enrollments.
Will I get a certificate after completing Cloud Computing?
Yes. Self-paced enrollment earns a course completion certificate once your final project is reviewed and approved. Internship enrollment earns an internship certificate once all 4 internship projects are approved. Live and Recorded enrollments earn both. Every certificate is publicly verifiable on our website and can be added directly to your LinkedIn profile.
What kind of projects will I build in Cloud Computing?
You'll work on real projects such as: Multi-tier web app on AWS & Azure — provision a load-balanced web, app, and database tier from one Terraform codebase across two clouds; Kubernetes microservices deployment — containerize a multi-service app and deploy it via Helm with rolling updates; CI/CD pipeline with automated testing — build a pipeline that lints, tests, builds, and deploys to staging on every merge; Observability stack with alerting — instrument a service with Prometheus/Grafana dashboards and page on SLO breach; DevSecOps pipeline with security gates — add SAST, dependency, and container scanning that blocks merges on critical findings.
