W7069G - IBM Watson OpenScale Methodology
You will learn how Watson OpenScale lets business analysts, data scientists, and developers build monitors for artificial intelligence (AI) models to manage risks. You will understand how to use Watson OpenScale to build monitors for quality, fairness, and drift, and how monitors impact business KPIs. You will also learn how monitoring for unwanted biases and viewing explanations of predictions helps provide business stakeholders confidence in the AI being launched into production. Note: This course contains the same topics as 6X240G IBM Watson OpenScale on IBM Cloud Pak for Data WBT.
Introduction to IBM Watson OpenScaleWatson OpenScale architectureGet started with Watson OpenScaleOverview of Watson OpenScale monitorsExplore a use caseBuild and configure the fairness monitorC
Analysts, Developers, Data Scientists and others who need to monitor machine learning jobs
1. Introduction to IBM Watson OpenScaleDescribe the problem that Watson OpenScale solvesDescribe models, monitors, workflowDescribe AIF and AIE 360 toolkitsDescribe workflow2. Watson OpenScale architecture Describe Watson OpenScale architecture on IBM Cloud and on IBM Cloud Pak for DataDescribe how Watson OpenScale works with other cloud services3. Get started with Watson OpenScaleProvision from catalogStart working with Watson OpenScale4. Overview of Watson OpenScale monitors Identify the different Watson OpenScale monitorsDefine how the different monitors are used5. Explore a use casePrepare the model for monitoring6. Build and configure the fairness monitorFeatures to monitorValues that represent a favorable outcome of the modelReference and monitored groupsFairness thresholdsSample sizeInsights and explainability7. Configure the quality monitorQuality alert thresholdSample size Insights and explainability8. Detect drift and configure the drift monitorAlert thresholdSample size Insights and explainability9. Configure application monitorsConfigure application monitorsConfigure KPI metrics in Watson OpenScaleConfigure event detailsAccess and visualize custom metrics
Basic knowledge of cloud platforms, for example IBM CloudBasic understanding of machine learning models, and how they are used
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