IBM Cloud Private for Data - Foundations - eLearning (6X134G) » zur vollständigen Seminarliste
This learning offering will tell a holistic story of IBM Cloud Private for Data including collaboration across an organization, which is key in this platform. Applicable to all personas. Four use cases will provide understanding of how organizations can benefit from IBM Cloud Private for Data. A variety of features will also be explored, providing students with the insight on how to use the platform.
If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.
Alle IBM Trainings werden mit Original IBM Schulungsunterlagen angeboten und finden in Kooperation mit dem von Arrow ECS autorisierten IBM Schulungspartner esciris statt.
IBM Cloud Private
• Describe the IBM Cloud Private platform
• Explain the IBM Cloud Private technical components
IBM Cloud Private for Data
• Describe the IBM Cloud Private for Data platform
• Explain the architecture and platform
• Explore four common use cases and their primary personas
• Describe the collaboration efforts in IBM Cloud Private for Data
Collaboration and workflows
• Describe the personas, roles and permissions in IBM Cloud Private for Data
• Describe a typical IBM Cloud Private for Data workflow
• Explore how each persona aligns within the workflow
• Explain the use case that will be used throughout the course
• 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
• Federate data
• Search and discover assets within IBM Cloud Private 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
• Manage the projects for analyzing data
• Explain the usage of notebooks
• Understand RStudio overview
• Create machine learning models
• Apply model management and deployment
Administer the platform
• Application administration tasks
• Cluster administration tasks
Data Engineer, Data Steward, Data Scientist, Business Analyst, Application Developer, Administrator.
- Digital Technical Engagement assets: IBM Cloud Private for Data
- General knowledge of IBM Cloud Private
Das Training findet auf Deutsch statt.