MLOps is used to scale and govern machine learning operations, while AIOps provides a way to solve business problems and reduce incident management overhead using AI.
In this course, you'll begin with an introduction to what AIOps is and which common IT operations it can be applied to. Discover AIOps capabilities, main business areas which AIOps can be incorporated into, and the benefits to an organization considering adoption. Next, explore various business use cases suitable for AIOps and adoption from a business and technical perspective.
Moving on, look at the capabilities provided by MLOps and the benefits of MLOps to a data scientist. Next, explore the steps involved in implementing MLOps including the tools, challenges, and best practices involved.
Upon completion of this course, you'll be able to identify the differences between AIOps, MLOps, and DevOps.
Learning Objectives
{"discover the key concepts covered in this course"}