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Course Outline
Introduction
Overview of Cloud Pak for Data Features and Architecture
- Red Hat OpenShift Container Platform.
- Containers, Kubernetes, and Helm.
- Red Hat OpenShift security.
Setting Up Cloud Pak for Data
- Pre-installation tasks.
- Installation.
- Post-installation tasks.
Setting Up Workflows
- Configuring roles and permissions for collaboration.
- Creating a workflow.
- Searching and requesting data.
Collecting Data
- Connecting to a data source.
- Adding data to a project.
Organizing Data
- Working with catalogs.
- Curating catalog data.
- Governing data to comply with regulations.
- Automating the discovery process.
Preparing Data
- Transforming data.
- Refining data.
- Virtualizing data.
Analyzing Data
- Analyzing data using notebooks.
- Analyzing data using other tools.
- Automatically analyzing data using AutoAI.
Implementing an AI Solution
- Building a machine learning model.
- Deploying the model.
- Validating the model.
- Monitoring the model.
Integrating Cloud Pak for Data with Other Services
- Finding services in a catalog.
- Finding services outside a catalog.
- Integrating IBM Cloud Pak for Data with other applications.
Administering Cloud Pak for Data
- Managing an IBM Cloud Pak for Data cluster.
- Managing an IBM Cloud Pak for Data web client.
- Uninstalling Cloud Pak for Data.
Troubleshooting
Summary and Conclusion.
Requirements
- Experience with data processing and AI concepts.
Audience
- Data Scientists.
- Business Analysts.
- Data Engineers.
- Developers.
- System Administrators.
14 Hours
Testimonials (2)
Doing Exercise
Joe Pang - Lands Department, Hong Kong
Course - QGIS for Geographic Information System
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
