You should have at least 2 years of experience in cloud architecture or DevOps, working knowledge of at least one major cloud platform (AWS, Azure, or GCP), familiarity with Docker and basic Kubernetes concepts, and an understanding of AI/ML model deployment fundamentals.

The curriculum covers multi-cloud infrastructure design for GenAI, GPU cluster management, serverless and container-based AI pipelines, model serving with auto-scaling, vector databases and feature stores, security and governance for AI workloads, cost optimization (FinOps), and unified monitoring across AWS, Azure, and GCP.

The program spans 16 weeks and is designed for working professionals. You should plan to dedicate approximately 10-15 hours per week, which includes video lessons, hands-on labs across all three cloud platforms, and project work.

You will complete three industry-relevant projects: building a multi-cloud GenAI model serving platform with failover and monitoring, designing an AI agent orchestration system using serverless backends and retrieval-augmented generation, and architecting a containerized GPU training pipeline with cross-cloud resource scheduling.

This program prepares you for high-demand roles such as Multi-Cloud Architect, GenAI Solutions Architect, and AI/ML Infrastructure Specialist. You will gain validated skills in designing production-grade GenAI infrastructure across all three major clouds, a capability increasingly sought by enterprises adopting multi-cloud AI strategies.

You will work extensively with AWS (Lambda, SageMaker, ECS, CloudWatch, Bedrock), Azure (Functions, Machine Learning, Container Apps, Monitor, OpenAI Service), and GCP (Cloud Run, Vertex AI, GKE, Cloud Monitoring). You will also use Docker, Kubernetes, vector databases, and infrastructure-as-code tools for multi-cloud deployment.

The Micro Degree course is an online LIVE course, where LIVE sessions will be conducted online on our Classroom platform. Prior to the start of the course, you'll receive preparatory material in the form of recorded content which can be access on the same platform.

In this course instructors will use English language for teaching.

Upon successful registration, you will receive a confirmation email on your registered email ID. In this email you will receive login details for your newly created account on the Edyoda Classroom platform (https://classroom.edyoda.com). Additionally, you will receive a PDF guide containing step-by-step instructions on how to utilize the platform to access live sessions and learning materials.

Our instructors are the industry experts with a minimum working experience of 10 years with a strong technical and teaching background. They bring industry knowledge and practical expertise to the course.

Yes, the course includes online assignments, quizzes, and a final project to reinforce your learning and assess your proficiency in Multi Cloud Architect for GenAI Infra.

Yes, you can interact with instructors and fellow students through discussion forums, live Q&A sessions. We encourage a supportive learning community.

We offer a 100% money-back guarantee to ensure your complete satisfaction. If you're not satisfied, you can request a full refund within 3 days of purchase or before the second session, whichever comes earlier. Simply contact our support team(support@edyoda.com) with your purchase details, such as the order ID or email address, and share your reason for the refund. Requests made after 3 days or after the second session will not be eligible for a refund. There are no hidden charges, you will receive the full amount paid. Refunds are processed within 7–10 business days and credited back to your original payment method.