Virtual Agent Development in Dialogflow ES for Citizen Devs
Welcome to "Virtual Agent Development in Dialogflow ES for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series.
What you'll learn
Welcome to "Virtual Agent Development in Dialogflow ES for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to develop customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will use Dialogflow ES to create virtual agents and test them using the Dialogflow ES simulator. This course also provides best practices on developing virtual agents. You will also be introduced to adding voice (telephony) as a communication channel to your virtual agent conversations. Through a combination of presentations, demos, and hands-on labs, participants learn how to create virtual agents. This is an intermediate course, intended for learners with the following types of roles: Conversational designers: Designs the user experience of a virtual assistant. Translates the brand's business requirements into natural dialog flows. Citizen developers: Creates new business applications for consumption by others using high level development and runtime environments. Software developers: Codes computer software in a programming language (e.g., C++, Python, Javascript) and often using an SDK/API. Prerequisite: Before taking this course, learners should have completed the "CCAI Conversational Design Fundamentals" course.
Table of contents
- Introduction 1m
- User Interface 1m
- Intents and entities 2m
- Actions and Responses 2m
- Training the agent 3m
- Advanced training 4m
- Testing tools 4m
- Knowledge 1m
- Best Practices 2m
- Lab Intro Dialogflow Fundamentals 0m
- Lab: CECCAI | Building a basic chat virtual agent (OD) 0m
- Lab Review Dialogflow Fundamentals 0m
- Lab Intro KB Connector 0m
- Lab: CECCAI | Creating a knowledge base connector (OD) 0m
- Lab Review KB Connector 1m
- Introduction 2m
- Context 2m
- Active versus inactive context 5m
- Input versus output context 6m
- Lifespan 3m
- Configuration 7m
- Follow-up 3m
- Best practices 4m
- Lab Intro Adding Contexts to your Virtual Agent 0m
- Lab: CECCAI | Adding context to your virtual agent (OD) 0m
- Lab Review Adding Contexts to your Virtual Agent 0m