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Course Description

  • This learning offering will tell a holistic story of Cloud Pak for Data including collaboration across an organization, which is key in this platform. Applicable to all personas. Multiple use cases will provide understanding of how organizations can benefit from Cloud Pak for Data. A variety of features will also be explored, providing students with the insight on how to use the platform.

Objectives

  • IBM Cloud Private 
    • Describe the IBM Cloud Private platform 
    • Explain the IBM Cloud Private technical components 

    Cloud Pak for Data 
    • Describe the Cloud Pak for Data platform 
    • Explain the architecture and platform 
    • Explore common use cases and their primary personas 
    • Describe the collaboration efforts in Cloud Pak for Data 

    Collaboration and workflows 
    • Describe the personas, roles and permissions in Cloud Pak for Data 
    • Describe a typical Cloud Pak for Data workflow 
    • Explore how each persona aligns within the workflow 
    • Explain the use case that will be used throughout the course 

    Access data 
    • Describe the differences between a data source and a data set 
    • Understand how to find the supported data sources 
    • Add and connect to a data source 
    • Add a data set to an analytics project 
    • Understand Data Virtualization 

    Organize data 
    • Search and discover assets within Cloud Pak for Data 
    • Request data you need for your project 
    • Understand data catalog and how to work with it 
    • Create and work with a data dictionary 
    • Explore and profile data 
    • Transform data with ETL 

    Analyze data 
    • Manage the projects for analyzing data 
    • Explain the usage of notebooks 
    • Understand RStudio overview 
    • Create machine learning models 
    • Apply model management and deployment 

    Add-ons and Integrations 
    • Describe Add-ons and Integrations 
    • Explore available Add-ons and Integrations 
    • Installing an Add-on 

    Administer the platform 
    • Application administration tasks 
    • Cluster administration tasks 
     

Audience

  • Data Engineer, Data Steward, Data Scientist, Business Analyst, Application Developer, Administrator

Prerequisites

  • requisite

  • Digital Technical Engagement assets: IBM Cloud Private for Data  (https://ibm-dte.mybluemix.net/ibm-cloud-private-for-data)
  • General knowledge of IBM Cloud Private

Content

  • IBM Cloud Private 
    • Describe the IBM Cloud Private platform 
    • Explain the IBM Cloud Private technical components 
    Cloud Pak for Data 
    • Describe the Cloud Pak for Data platform 
    • Explain the architecture and platform 
    • Explore common use cases and their primary personas 
    • Describe the collaboration efforts in Cloud Pak for Data 
    Collaboration and workflows 
    • Describe the personas, roles and permissions in Cloud Pak for Data 
    • Describe a typical Cloud Pak for Data workflow 
    • Explore how each persona aligns within the workflow 
    • Explain the use case that will be used throughout the course 
    Access data 
    • Describe the differences between a data source and a data set 
    • Understand how to find the supported data sources 
    • Add and connect to a data source 
    • Add a data set to an analytics project 
    • Understand Data Virtualization 
    Organize data 
    • Search and discover assets within Cloud Pak for Data 
    • Request data you need for your project 
    • Understand data catalog and how to work with it 
    • Create and work with a data dictionary 
    • Explore and profile data 
    • Transform data with ETL 
    Analyze data 
    • Manage the projects for analyzing data 
    • Explain the usage of notebooks 
    • Understand RStudio overview 
    • Create machine learning models 
    • Apply model management and deployment 
    Add-ons and Integrations 
    • Describe Add-ons and Integrations 
    • Explore available Add-ons and Integrations 
    • Installing an Add-on 
    Administer the platform 
    • Application administration tasks 
    • Cluster administration tasks 


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