DevOps to MLOps: Unlock the Future of AI and Cloud Careers

Are you a DevOps Engineer, Cloud Professional, or AI Enthusiast looking to transition into the high-demand field of MLOps? This course is designed to help you bridge the gap between DevOps and AI Operations (AIOps) by equipping you with practical skills and real-world use cases.In this course, you will:Understand the evolution from DevOps to MLOps and why AI-driven workflows are the future.Learn Kubernetes, Terraform, and CI/CD pipelines tailored for AI/ML model deployment.Implement real-world projects on AWS, Azure, and GCP using Dockerized ML models.Master end-to-end automation of Machine Learning pipelines with GitOps, ArgoCD, and Kubeflow.Deploy AI models efficiently using feature stores, model registries, and cloud-native monitoring.Who is this course for?DevOps and Cloud Engineers looking to pivot into MLOps & AI OperationsSoftware Engineers eager to automate Machine Learning pipelinesData Scientists interested in productionizing AI modelsAI & ML professionals who want to scale deployments with Kubernetes and TerraformWhat makes this course unique?100% Hands-on Labs with real-world MLOps projectsIndustry Best Practices from top tech companiesCI/CD Pipelines for AI/ML models using Terraform, Kubernetes, and Cloud servicesIntegrations with AWS SageMaker, Azure ML, and GCP AIJoin now and unlock the future of DevOps & MLOps careers!