Cloud + AI
Cloud + AI Infrastructure
AWS, Azure and GCP with serverless, Kubernetes and AI infrastructure.
14 weeks Beginner to Advanced
Online LiveRecorded Course
How to Become a Cloud Engineer
Where does software actually run?
With AI: Cloud + AI Infrastructure Engineer
What You Do
- Design compute
- Manage storage
- Configure networking
- IAM & access
- Containers and serverless
Core Skills
- AWS
- Microsoft Azure
- Google Cloud
- Linux
- Kubernetes
- Networking
- IAM
AI Advantage
- Deploy LLM applications
- RAG systems
- Vector databases
- AI APIs
- AI agents
Fundamentals + AI, Not AI Instead of Fundamentals
AI can generate code, SQL, scripts, test cases and documentation, but a Cloud Engineer still needs strong fundamentals and the judgement to verify AI output. Start with your role, build fundamentals, add AI, build projects and keep learning.
Courses to Become a Cloud Engineer
Cloud + AI
DevOps + AI (AIOps)
Linux, Git, CI/CD, Docker, Kubernetes, Terraform, cloud and AIOps.
16 weeks Beginner to Advanced
Online LiveRecorded Course