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Guide to Watson Cognitive APIs

In this course, you will learn the fundamentals of creating, configuring, and training the Watson cognitive services on the IBM Cloud. Using these robust APIs, you will learn to harness the power of Watson in your applications.
For each service, you will start by learning its features and functionality. Then, we will guide you through creating and configuring the service on your own. Finally, after learning about the service, you will be challenged to integrate the service into an application. We’ll provide an application and a set of requirements, and you’ll use what you’ve learned to extend the application to meet a business need.
On the last day of class, you will have an opportunity to experiment with combining multiple Watson services to create powerful, intelligent applications.

Derivative Works Courses are developed by an IBM authorized Global Training Provider. The content of the course is based on IBM products and services. It offers skills or services that IBM does not offer in the course catalog today and are intended to compliment our existing portfolio. The course is developed by the Training Provider. IBM solely provides a market place to advertise the courses on our external websites, ibm.com/training and lists the Global Training Provider who owns the content.

Profil uczestnika

  • Application Developers, Solution Designers, and Product Owners 


1. Introduction to Watson Services
1.1. Introduction
1.2. IBM Cloud
1.3. Cognitive computing
1.4. Watson Developer Cloud
1.5. Set up your development environment
2. Watson Tone Analyzer
2.1. Overview
2.2. Practive: Create a Watson Tone Analyzer service and review sample analyses
2.3. Using the API
2.4. Challenge: Build a customer tone detector with Tone Analyzer
3. Watson Coversation
3.1. Overview
3.2. Practice: Develop a chatbot version of yourself
3.3. Using the API
3.4. Challenge: Automate responses to customer inquiries with Watson Coversation
4. Node-RED Starter
4.1. Overview
4.2. Practive: Build a “hello world” application with Node-RED Starter
5. Watson Personality Insights
5.1. Overview
5.2. Practice: Create a Watson Personality Insights service and review sample personality profiles
5.3. Using the API
5.4. Challenge: Analyze cover letters with Personality Insights
6. Watson Natural Language Classifier
6.1. Overview
6.2. Practive: Create, configure, and test the Natural Language Classifier
6.3. Using the API
6.4. Challenge: Classify customer inquiries using Natural Language Classifier
7. Watson Language Translator
7.1. Overview
7.2. Practive: Create, configure, and test the Language Traslator
7.3. Using the API
7.4. Challenge: Classify customer inquiries using Language Traslator
8. Watson Visual Recognition
8.1. Overview
8.2. Practive: Create a custom image classifier
8.3. Using the API
8.4. Challenge: Build an image tagging tool with Watson Visual Recognition
9. Watson Speech to Text
9.1. Overview
9.2. Create a Watson Speech to Text service and review sample output
9.3. Using the API
9.4. Challenge: Build an audio transcription application using Watson Speech to Text
10. Watson Text to Speech
10.1. Overview
10.2. Create a Watson Text to Speech service and reivew sample output
10.3. Using the API
10.4. Challenge: Build text to audio application using Watson Text to Speech
11. Watson Natural Language Understanding
11.1. Overview
11.2. Practice: Create a Natural Language Understanding service and review sample output
11.3. Using the API
11.4. Challenge: Perform market research with Natural Language Understanding
12. Watson Discovery
12.1. Overview
12.2. Practice: Query and analyze speeches by U.S. Presidents with the Discovery service
12.3. Using the API
12.4. Challenge: Build a cognitive search tool with Discovery
13. Watson Coversation with Discovery
13.1. Overview
13.2. Practice: Create a frequently asked questions chatbot with Coversation and Discovery
14. Final Challenge and Conculsion
14.1. Conclusion
14.2. Challenge: Solve a business problem with Watson Services

Wymagane przygotowanie uczestników

• Basic understanding of the IBM Cloud Platform (recommended)
• At least one or more programming languages, such as Java, Node.js, C#, Python, Ruby, GO, although no specific language is required to complete this course
• Common data structures such as string, integer, and array
• Base understanding of JSON and REST APIs
• Source code control principles in Git-compatible services


• Create and configure Watson cognitive services
• Use Watson cognitive APIs in a front-end application
• Combine Watson cognitive services
• Identify use cases for Watson cognitive services
• Build data flows with Node-RED

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