The MLOps course teaches you how to streamline the entire Machine Learning lifecycle from development to production. You will learn model versioning, automated training pipelines, CI/CD for machine learning, model containerization using Docker/Kubernetes, and tracking drift/performance in live environments using tools like MLflow, Kubeflow, and DVC.
Bridge the gap between ML models and production by mastering CI/CD pipelines, model tracking, automation, and monitoring.
Download the course curriculum PDF or contact us for the complete training plan.
03 WEEKS Automate deployment pipelines and manage cloud infrastructure at scale using advanced AWS DevOps tools.
03 WEEKS Secure cloud data and workloads with advanced security controls, compliance frameworks, and identity management on AWS.
03 WEEKS Master architectural principles and services on AWS to design secure, robust, and cost-effective cloud infrastructures.
03 WEEKS Gain hands-on operational expertise in deploying, managing, and operating scalable systems on AWS.
