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6X240G – IBM Watson OpenScale on IBM Cloud Pak for Data (V2.5.x)

Home / 6X240G – IBM Watson OpenScale on IBM Cloud Pak for Data (V2.5.x)

Course Outline:

Introduction to IBM Watson OpenScale
- Describe the problem that Watson OpenScale solves
- Describe models, monitors, workflow
- Describe AIF and AIE 360 toolkits
- Describe workflow

IBM Watson OpenScale architecture
- Describe OpenScale architecture on IBM Cloud and on IBM Cloud Pak for Data
- Describe how Watson OpenScale works with other cloud services

Get started with IBM Watson OpenScale on IBM Cloud Pak for Data
- Install the Watson OpenScale service
- Work with Watson OpenScale on Cloud Pak for Data

Overview of Watson OpenScale monitors
- Identify the different Watson OpenScale monitors
- Describe how the monitors are used

Explore a use case
- Prepare the model for monitoring

Build and configure the fairness monitor
- Features to monitor
- Values  that represent a favorable outcome of the model
- Reference and monitored groups
- Fairness thresholds
- Sample size
- Insights and explainability

Configure the quality monitor
- Quality alert threshold
- Sample size
- Insights and explainability

Detect drift and configure the drift monitor
- Alert threshold
- Sample size
- Insights and explainability

Configure application monitors
- Configure application monitors
- Configure KPI metrics in Watson OpenScale
- Configure event details
- Access and visualize custom metrics

Course Audience & Prerequisites:

Audience:

Analysts, Developers, Data Scientists and others who need to monitor machine learning jobs

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 (V2.5.x): Foundations - 6X236G (recommended)

Course Offerings:

This IBM Web-Based Training (WBT) is Self-Paced and includes:
- Instructional content available online for duration of course
- Visuals without hands-on lab exercises

  • Course Outline
  • Course Audience & Prerequisites
  • Course Offerings
  • Related Courses

Introduction to IBM Watson OpenScale
- Describe the problem that Watson OpenScale solves
- Describe models, monitors, workflow
- Describe AIF and AIE 360 toolkits
- Describe workflow

IBM Watson OpenScale architecture
- Describe OpenScale architecture on IBM Cloud and on IBM Cloud Pak for Data
- Describe how Watson OpenScale works with other cloud services

Get started with IBM Watson OpenScale on IBM Cloud Pak for Data
- Install the Watson OpenScale service
- Work with Watson OpenScale on Cloud Pak for Data

Overview of Watson OpenScale monitors
- Identify the different Watson OpenScale monitors
- Describe how the monitors are used

Explore a use case
- Prepare the model for monitoring

Build and configure the fairness monitor
- Features to monitor
- Values  that represent a favorable outcome of the model
- Reference and monitored groups
- Fairness thresholds
- Sample size
- Insights and explainability

Configure the quality monitor
- Quality alert threshold
- Sample size
- Insights and explainability

Detect drift and configure the drift monitor
- Alert threshold
- Sample size
- Insights and explainability

Configure application monitors
- Configure application monitors
- Configure KPI metrics in Watson OpenScale
- Configure event details
- Access and visualize custom metrics

Audience:

Analysts, Developers, Data Scientists and others who need to monitor machine learning jobs

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 (V2.5.x): Foundations - 6X236G (recommended)

This IBM Web-Based Training (WBT) is Self-Paced and includes:
- Instructional content available online for duration of course
- Visuals without hands-on lab exercises