As more and more organizations embrace AI for increasingly critical decisions, having the ability to observe, assess, and explain why decisions are made at both a macro and micro level will become essential. In this course, AIOps: Observability and Explainability for Production Models, you’ll learn the tools and techniques that make this possible. First, you’ll explore why explainability is such a critical capability for a successful model, both in terms of justifying specific decisions as well as demonstrating fairness and lack of bias. Next, you’ll discover where various observability tools fit in the development lifecycle and operation of a production model. Finally, you’ll learn how to visualize, share, and operationalize your observability approach. When you finish this course, you'll have the knowledge necessary to pursue operationalizing your production AI models with greater assurance that your models are fair and accurate and can be explained to any audience.
Overview
As more and more organizations embrace AI for increasingly critical decisions, having the ability to observe, assess, and explain why decisions are made at both a macro and micro level will become essential. In this course, AIOps: Observability and Explainability for Production Models, you’ll learn the tools and techniques that make this possible. First, you’ll explore why explainability is such a critical capability for a successful model, both in terms of justifying specific decisions as well as demonstrating fairness and lack of bias. Next, you’ll discover where various observability tools fit in the development lifecycle and operation of a production model. Finally, you’ll learn how to visualize, share, and operationalize your observability approach. When you finish this course, you'll have the knowledge necessary to pursue operationalizing your production AI models with greater assurance that your models are fair and accurate and can be explained to any audience.
Taught by
Russ Thomas
