MLOps Certification Training

Machine Learning Operations (MLOps) Certification Course is a comprehensive, instructor-led program designed to help professionals streamline the deployment, monitoring, and management of machine learning models in production environments. Over the span of 5.5 weeks, held on weekends, you will explore the complete MLOps lifecycle—covering important topics such as version control, containerization with Docker, orchestration with Kubernetes, CI/CD pipelines, model management through tools like MLflow and Kubeflow, and monitoring with Prometheus and WhyLogs.

The MLOps Certification Training curriculum integrates both DevOps and ML disciplines, providing hands-on labs using AWS SageMaker, Azure ML, and cloud-agnostic setups, along with real-world capstone projects like automated deployment pipelines and dynamic model monitoring. With 24/7 support, lifetime access to updated materials, and live doubt-clearing sessions, this course is perfect for developers, data scientists, and engineers looking to enhance their workflows from experimentation to scalable, production-level solutions.

Upon completion, validated through quizzes and assignments, participants will receive a certificate that demonstrates their proficiency in deploying robust, reproducible ML systems. This credential will position them for roles such as MLOps Engineer, Lead, or Architect in today’s AI-driven industry.