Cloud Engineering
Google Cloud and Microsoft Azure
- IAM, networking and compute
- Storage, databases and serverless
- Monitoring and architecture
A practical learning platform with live classes, recorded lessons, guided labs, portfolio projects, mentor support and interview preparation.
Share your details and we will help you choose the right program.
Each program combines concepts, labs, projects and deployment experience.
Google Cloud and Microsoft Azure
Linux, Git, Docker, Kubernetes and CI/CD
Python, ML pipelines and cloud deployment
Technology, problem-solving and client delivery
The curriculum follows a clear path from foundations to implementation, troubleshooting, projects and production deployment.
Linux, networking, Git, scripting basics, cloud concepts and development fundamentals.
GCP, Azure, IAM, VPC/VNet, compute, storage, databases, load balancing and monitoring.
Maven, Nexus, SonarQube, Docker, Kubernetes, CI/CD, security and observability.
Capstone implementation, GitHub portfolio, resume support, mock interviews and deployment.
Students build complete applications and infrastructure workflows suitable for a portfolio.
Deploy a multi-tier application with domain mapping, HTTPS, database and monitoring.
Build, test, scan, publish and deploy an application using a complete delivery pipeline.
Deploy a scalable application with services, ingress, secrets and health checks.
Student: How should I connect my application securely to the database?
Mentor: Let us review your architecture and configure the private connection step by step.
Get guidance for labs, troubleshooting, projects, architecture decisions and career preparation.
Access your recorded classes, course notes, assignments, projects and progress dashboard.
Open Demo DashboardYes. The learning path starts with fundamentals before progressing to advanced implementation.
Yes. Students can access uploaded Zoom class recordings from their course portal.
Yes. Each track contains labs, assignments and portfolio-level projects.
No. SkillOps Academy will also include MLOps, Python, FastAPI and FDE learning paths.