When does class start/end?
Classes begin promptly at 9:00 am, and typically end at 5:00 pm.
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 This learning offering will tell...Read More
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
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. A generic use case 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. This WBT contains instructional and interactive content, demonstrations and hands-on exercises (on Cloud Pak for Data on IBM Cloud).
- Introduction to IBM Cloud Pak for Data - Red Hat OpenShift Container Platform: overview- Collaboration and workflows - Collect data - Organize data- Prepare data - Analyze data - Infuse data- Assessment
Data Engineer, Data Steward, Data Scientist, Business Analyst, Application Developer, Administrator
IBM Demo assets: IBM Cloud Pak for Data, in particular Overview Cloud Pak for Data (https://www.ibm.com/demos/collection/Cloud-Pak-for-Data/)
Introduction to IBM Cloud Pak for Data - Describe IBM Cloud Pak for Data - Identify how IBM Cloud Pak for Data makes you ready for artificial intelligence (AI) - Describe, at a high level, the IBM Cloud Pak for Data architecture- Describe how to collaborate within IBM Cloud Pak for Data - Describe the typical end-to-end data and analytics workflow in IBM Cloud Pak for Data- Identify what you will be doing in this training Red Hat OpenShift Container Platform: overview- Describe how the Red Hat OpenShift Container Platform relates to IBM Cloud Pak for Data- Describe the role of containers, Kubernetes, and Helm- Describe how Red Hat OpenShift is a layered system- Describe, at a high level, the Red Hat OpenShift architecture- Describe, at a high level, how Red Hat OpenShift is secured Collaboration and workflows - Administer the platform- Describe a typical workflow- Create an analytics project - Search for data- Request data Collect data - Identify how you connect to data sources in IBM Cloud Pak for Data - Identify ways in which you can add data to a project- Identify supported data sources - Describe how to work with an integrated database - Create a connection to a data source Organize data- Describe the Watson Knowledge Catalog service and what you can do with it - Describe how you can work with catalogs - Describe how you can govern and curate data using Watson Knowledge Catalog - Identify how governance artifacts and governance tools work together- Identify how you can govern data to comply with regulations- Perform automated discovery and work with the default catalog Prepare data - Identify ways in which you can prepare data for use in projects - Describe how to virtualize data using the Data Virtualization service- Describe how you can refine data using the Data Refinery service- Identify how you can access trusted master data with IBM Master Data Connect- Describe how you can build trust in unstructured data with IBM Watson Knowledge Catalog Instascan- Identify how you can manage test data using Virtual Data Pipeline (VDP) Analyze data - Identify how you can analyze data in IBM Cloud Pak for Data - Automate building machine learning models with AutoAI experiment - Deploy machine learning models- Analyze data using notebooks- Identify other tools that you can use to analyze data Infuse data- Identify how you can perform self-service analytics with Cognos Analytics- Describe how you can extract answers from complex business documents with Watson Discovery- Identify how you can deliver engaging, unified problem-solving experiences with Watson Assistant- Describe you can accurately transcribe the human voice with Watson Speech to Text- Identify how you can convert written text to natural-sounding speech with Watson Text to Speech- Describe how you can automate planning, budgeting, and forecasting with Planning Analytics Assessment