Technology, Data and Science

MLOps Essentials: Model Deployment and Monitoring

Machine learning operations (MLOps) is one of the fastest growing subfields of artificial intelligence. As more and more models have been deployed in production, the need for a structured, agile, end-to-end, automated machine learning lifecycle has continued to grow. In this course, instructor Kumaran Ponnambalam shows you how to apply key concepts from MLOps to create structured, improved outcomes in your everyday workflow.

Explore the fundamentals of MLOps to get up and running on your next machine learning project. Find out why so many data scientists, engineers, and project managers are so excited about ML models, as you discover the ins and outs of successfully deploying and monitoring models on your own. From continuous delivery to model serving and continuous monitoring to drift management, Kumaran equips you with the skills you need to start practicing effective, fair, explainable, and responsible artificial intelligence.

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