AIOps: Observability and Explainability for Production Models
Learn AI explainability & observability for trustworthy production AI. Implement tools & techniques to understand & monitor your AI pipelines. Essential skills for the AI future.
Course Content
AIOps: Observability and Explainability for Production Models is an intermediate-level Pluralsight course taught by Russ Thomas. It runs 20m, is taught in English, and includes a certificate of completion. It is a paid course, first published February 2025.
As organizations increasingly rely on AI for critical decisions, the ability to observe, assess, and explain those decisions – at both a broad and granular level – is becoming paramount. This course, AIOps: Observability and Explainability for Production Models, equips you with the essential tools and techniques to achieve this.
You'll delve into why explainability is crucial for successful AI models. Understand how it's vital for justifying specific outcomes and ensuring fairness and mitigating bias in your AI deployments.
Next, you'll map out the role of various observability tools throughout the entire development lifecycle and ongoing operation of production models. Learn how these tools provide insights into model behavior.
Finally, master the process of visualizing, sharing, and operationalizing your observability approach. Gain practical skills to make your AI models more transparent.
Upon completion, you'll possess the knowledge to confidently operationalize production AI models, ensuring they are fair, accurate, and readily explainable to any stakeholder. Learn how to build trust and accountability in your AI systems.
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