When does class start/end?
Classes begin promptly at 9:00 am, and typically end at 5:00 pm.
Course DescriptionThis course provides attendees with instruction to learn about AI and IBM Watson services for individual learning, and product skills enablement.Instruction is provided on the...Read More
This course provides attendees with instruction to learn about AI and IBM Watson services for individual learning, and product skills enablement.
Instruction is provided on the following, as well as other related topics:
• AI concepts including Cognitive Computing, Machine Learning, Supervised Learning, Unsupervised Learning, Reinforcement Learning and Neural Networks
• Watson Services, their APIs and use cases including: Conversational Agent (now Watson Assistant), Natural Language Classifier, Language Translation, Personality Insights, Speech to Text, Text to Speech, Tone Analyzer, Visual Recognition, Watson Discovery, Watson Knowledge Studio, and others
• Introduction to IBM Cloud
This course is designed for application developers and IT Professionals who need to quickly acquire skills to understand and work with Watson services.
Although not mandatory, having the following skills will greatly assist with understanding the concepts in this course:
• Working knowledge of AI concepts such as intent, relationships, entities, and ground truth
• Basic knowledge of machine learning methods and technologies
• Working knowledge of developing an application using IBM Watson AI services
• Working knowledge of core IBM Cloud services (monitoring, logging, scaling), and security
• Working knowledge with designing, developing and deploying RESTful APIs
• Working knowledge of use cases using IBM Watson AI services
• Working knowledge of the application starter kits and demos available on the IBM Cloud
• Working knowledge of open technologies like Cloud Foundry, IBM Cloud and Git like repositories
After completing this course, you should be able to:
• Understand AI basic concepts including cognitive computing, machine learning, supervised learning, unsupervised learning, reinforcement learning, fitting a model, training, validation and test data, and evaluating a model.
• Understand the following IBM Watson AI services, their use cases, and combining these for choreographed solutions:
o Watson Assistant
o Natural Language Classifier
o Language Translation
o Personality Insights
o Speech to Text
o Text to Speech
o Tone Analyzer
o Visual Recognition
o Watson Discovery
o Watson Knowledge Studio
• Create an account on IBM Cloud
• Create and invoke IBM Watson services on IBM Cloud
• Use Tooling to work with IBM Watson services
• Use APIs to work invoke IBM Watson services
• Understand the purpose of Watson SDKs
• Understand the process of obtaining credentials for Watson AI services on IBM Cloud
• Understand application logging on IBM Cloud