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IBM Watson OpenScale for IBM Cloud Pak for Data (V3.0.x) eLearning

Course content updated by LearnQuest
Price
239 USD
6 Hours
6X340GW
Self-Paced Training (WBT)
IBM Business Partner
Prices reflect a 22.5% discount for IBM employees.
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Course Description

Overview

This offering teaches you how IBM Watson OpenScale for IBM Cloud Pak for Data lets business analysts, data scientists, and developers build monitors for machine learning (ML) models to manage risks. You will understand how to use Watson OpenScale to build monitors for quality, fairness, and drift. You will also learn how explanations of predictions helps provide business stakeholders confidence in the AI being launched into production.

Objectives

• Introduction to IBM Watson OpenScale 
• IBM Watson OpenScale technical architecture 
• Get started with IBM Watson OpenScale on IBM Cloud Pak for Data 
• Overview of Watson OpenScale monitors 
• Explore a use case for Watson OpenScale 
• Configure a quality monitor 
• Configure a fairness monitor 
• Detect drift and configure the drift monitor 
• Monitor a deployed model in production

Audience

Business Analysts, Data Scientists, Developers, Researchers, and others who need to monitor machine learning models

Prerequisites

    • Basic knowledge of cloud platforms, for example IBM Cloud  
    • Basic understanding of machine learning models, and how they are used 
    • IBM Cloud Pak for Data (V3.0.x): Foundations - 6X336G (recommended) 

Topics

Introduction to IBM Watson OpenScale 
• Describe the problem that Watson OpenScale solves 
• Describe how Watson OpenScale can help 
• Explain important terms in the contect of trust in AI 

IBM Watson OpenScale technical architecture 
• Describe Watson OpenScale architecture for IBM Cloud Pak for Data 
• Describe Watson OpenScale components and services 
• Describe the various types of data 

Get started with IBM Watson OpenScale on IBM Cloud Pak for Data 
• Describe the Watson OpenScale system setup 
• Describe the Watson OpenScale data mart 
• Set up a machine learning provider 
• Specify the model details 

Overview of Watson OpenScale monitors 
• Identify the different Watson OpenScale monitors 
• Describe explanations 

Explore a use case for Watson OpenScale 
• Describe how Watson OpenScale can provide trust in AI in a credit risk example 

Configure a quality monitor 
• Describe the type of data required to monitor quality 
• Explain quality metrics for categorical labels 
• Explain quality metrics for quantative labels 
• Configure a quality monitor 
• Explain predictions 

Configure a fairness monitor 
• Explain the idea behind assessing fairness 
• Describe the type of data required to monitor fariness 
• Configure a fairness monitor 

Detect drift and configure the drift monitor 
• Describe the two types of drift 
• Describe the type of data required to monitor fariness 
• Configure a drift monitor 

Monitor a deployed model in production 
• Put a model monitor into production 
• Provide feedback data for the quality monitor 
• Provide payload data for the fairness and drift monitor

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Self-Paced Training Info

Learn at your own pace with anytime, anywhere training

  • Same in-demand topics as instructor-led public and private classes.
  • Standalone learning or supplemental reinforcement.
  • e-Learning content varies by course and technology.
  • View the Self-Paced version of this outline and what is included in the SPVC course.
  • Learn more about e-Learning

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Self-Paced Training Terms & Conditions

IBM WEB BASED TRAINING (WBT) IS SELF-DIRECTED AND SELF-PACED. Before you enroll, review the system requirements to ensure that your system meets the minimum requirements for this course. AFTER YOU ARE ENROLLED IN THIS COURSE, YOU WILL NOT BE ABLE TO CANCEL YOUR ENROLLMENT. You are billed for the course when you submit the enrollment form. Web Based Training courses are non-refundable. Once you purchase a Web Based Training course, you will be charged the full price.

IBM Web Based Training courses are sold on a per-user basis. WBT courses provide a training advantage for you and your teams, helping you get up to speed quickly. Take the courses you need, at your convenience and at your own pace.

You can start the course at any time within 12 months of enrolling for the course. After you register/start the course, you have 30 days to complete your course. Within this 30 days, the self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day.

System Requirements

To participate in this course, the student workstation must meet the following hardware requirements:
  • Minimum of 256 MB of memory
  • Windows Vista or Windows 7-10 (32-bit or 64-bit edition)
  • Internet Explorer 6 or higher or Firefox ESR
  • 128-bit encryption
  • Citrix Receiver for connection to the IBM Remote Lab Platform
  • Java
  • Access to Internet with at least 128 kbps down and 128 kbps up
  • Other platforms/combinations may work but are not officially supported by IBM.

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