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Course Description
This IBM AI Course is designed to help students prepare and enable themselves on the Watson services on Cloud.
Objectives
This intermediate level technical professional is an individual who understands concepts essential to the development of applications using IBM Watson AI services. They will have experience using the IBM Cloud and are able to consume IBM Watson AI services in an application. This individual is able to perform these tasks with little to no assistance from product documentation, support or peers.
Key Areas of Competency:
- Fundamentals of IBM Watson AI services on IBM Cloud
- Use cases of Artificial Intelligence and Machine Learning
- Developing AI applications using IBM Watson AI services
- Administering applications using IBM Watson AI services
Audience
Prerequisites
This IBM Artificial Intelligence Course requires -
- Working knowledge of developing an application
- Working knowledge of core Cloud services (monitoring, logging, scaling), and security
- Working knowledge with designing, developing and deploying RESTful APIs
- Working knowledge of cognitive concepts such as intent, relationships, entities, and ground truth
- Working knowledge of open technologies like CloudFoundry and Git like repositories
- Basic knowledge of application development using common web technologies such as Node.js, Javascript, HTML, and css
Content
Day 1 : Section 1 - Fundamentals of Artificial Intelligence (AI) Computing
- Define the main characteristics of an AI system.
- Explain neural nets.
- Explain Machine Learning technologies (supervised, unsupervised, reinforcement learning approaches).
- Define a common set of use cases for AI systems.
- Define Precision, Recall, and Accuracy
- Explain the importance of separating training, validation and test data.
- Measure accuracy of a Watson AI service.
- Perform Domain Adaption using Watson Knowledge Studio (WKS).
- Define Intents and Classes.
- Identify the difference between the user question and the user intent.
Section 2 - Use Cases for Artificial Intelligence
- Select an appropriate combination of AI technologies based on use-case and data format.
- Explain the uses of the Watson AI services in the Starter Kits.
- Describe the Watson Conversational Agent.
- Explain use cases for integrating external systems (such as Twitter, Weather API).
- Describe the IBM Watson Discovery Service
Day 2 : Section 3 - Fundamentals of IBM Watson AI services
- Distinguish the Watson AI services on IBM Cloud for which training is required.
- Provide examples of text classification using the NLC.
- Explain the Watson SDKs available as part of the Watson AI services on IBM Cloud.
- Explain the Watson REST APIs available as part of the Watson AI services on IBM Cloud.
- Explain and configure the Natural Language Classification service.
- Explain and configure the Visual Recognition service.
- Explain how the Personality Insights service works.
- Explain how the Tone Analyzer service works.
- Explain and execute IBM Watson Natural Language Understanding service.
- Explain, setup, configure and query the IBM Watson Discovery service.
- Explain and configure the IBM Watson Assistant service
Day 3 : Section 4 - Developing AI applications using IBM Watson AI Services on IBM Cloud
- Call a Watson API to analyze content.
- Describe the tasks required to implement the Conversational Agent / Digital Bot.
- Transform service outputs for consumption by other services.
- Define common design patterns for composing multiple Watson services together (across APIs).
- Design and execute a use case driven service choreography (within an API).
- Explain the process to provision and use an instance of an IBM Watson AI service instance on IBM Cloud.
- Explain the advantages of using IBM Cloud as the cloud platform for AI application development and deployment.
Day 4: Section 5 Administration & DevOps for applications using IBM Watson AI services on IBM Cloud
- Describe the process of obtaining credentials for Watson AI services on IBM Cloud.
- Examine application logs provided on IBM Cloud.