Developing AI and machine learning models is just the first step to keeping AI and ML systems performing and providing their needed value to the organization. In addition, organizations are realizing the need to manage models produced by other parts of their organization of third-parties. The developing area of Machine Learning Operations (ML Ops) and additional aspects of machine learning lifecycle management has emerged to address these needs. The Managing the AI & ML Lifecycle: “ML Ops” and Beyond course provides a foundational overview of AI & ML lifecycles, concepts around MLOps, deep dive into each of the aspects of AI & ML lifecycle management, details on ML Ops needs and capabilities, and provides a guidebook for managing ML projects as they continue to iterate, as well as steps and practical guidance for how to adopt an MLOps game plan at your organization to ensure success. This course provides a certification upon successful completion, has no prerequisites, and is appropriate for people with different roles and levels of expertise.

Total Training Hours: Twenty four (24) hours of instruction plus exercises

24 May - 27 May 2022, All Day