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 In this 6 hour web-based...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
In this 6 hour web-based training (WBT), you will learn how Watson Discovery lets business analysts and developers rapidly build cognitive, cloud-based exploration applications that unlock actionable insights hidden in unstructured data - including your own proprietary data, as well as public and third-party data.
- Discovery overview: Architecture of Watson Discovery- Discovery overview: Administering security in Watson Discovery- Discovery overview: Creating a collection- Configuring a Discovery collection- Ingesting data into a Discovery collection- Querying a Discovery collection- Querying a Discovery collection: Relevancy training- Querying a Discovery collection: Passage retrieval
Analysts, Developers, and others who need to monitor machine learning jobs
- Basic knowledge of cloud platforms, for example IBM Cloud - Basic understanding of enterprise search and natural language
Discovery overview: Architecture of Watson Discovery- Describe Discovery architecture in a cloud environment- Describe content creation within Discovery- Describe Discovery data collection runtime flows- Describe Discovery user runtime flows Discovery overview: Administering security in Watson Discovery- List types of security used in Watson Discovery on Cloud- Describe how Discovery service credentials are used- Describe a common use case for securing private data within Discovery Discovery overview: Creating a collection- Instantiate Watson Discovery- Connect to a Discovery instance- Create a collection Configuring a Discovery collection- Configure enrichments for a paticular business case- Use tooling and APIs to configure a Discovery collection- Use Smart Document Understanding to identify fields from documents Ingesting data into a Discovery collection- Describe use cases for using APIs, tooling and data sources to ingest data- Describe the steps for ingesting documents into Discovery- Perform ingestion operations such as add, update and delete documents- Describe ingestion limitations Querying a Discovery collection- Explain simple, combined and aggregate queries- Explain search and structure parameters, operators and aggregation types for querying a collection- Use the Discovery query language for constructing queries Querying a Discovery collection: Relevancy training- Explain the purpose of relevancy training- Detail the process of using relevancy training for improving results Querying a Discovery collection: Passage retrieval- Explain the purpose of passage retrieval- Describe passage retrieval settings and usage- Use passage retrieval to return pointed results