Course Description

Course Overview

The Customer Experiences with Contact Center AI – Dialogflow ES (CCAIDES) course is designed to provide individuals with the knowledge and skills necessary to design and develop conversational AI solutions using Dialogflow ES in contact center environments. This course focuses on the key concepts, tools, and best practices for building intelligent virtual agents and chatbots to enhance customer experiences and improve contact center efficiency.

Prerequisites

To enroll in the CCAIDES course, participants should have a basic understanding of conversational AI concepts and experience with web development principles. Familiarity with Dialogflow ES and GCP fundamentals will be beneficial. Participants should have access to a GCP project or demo environment to practice the concepts covered in the course.

Methodology

The CCAIDES course follows a blended learning approach, combining theoretical instruction, demonstrations, discussions, and hands-on labs. Participants will engage in instructor-led sessions where conversational AI concepts, best practices, and Dialogflow ES features are explained. They will also have access to resources and tools to gain practical experience in designing and developing virtual agents and chatbots using Dialogflow ES. The course encourages active participation, discussions, and collaborative problem-solving to reinforce learning.

Course Outline

Introduction to Conversational AI and Contact Center AI

Overview of conversational AI and its applications in contact centers

Understanding the benefits of Contact Center AI and Dialogflow ES

Exploring Dialogflow ES features for building conversational agents

Designing Virtual Agents with Dialogflow ES

Analyzing customer intents and designing conversational flows

Implementing entities and contexts for dialogue management

Enhancing virtual agent interactions with fulfillment and webhooks

Natural Language Understanding with Dialogflow ES

Training and improving the performance of intent recognition models

Utilizing Dialogflow’s machine learning capabilities for language understanding

Implementing custom entity recognition and slot filling

Integrating Dialogflow ES with Contact Center Platforms

Configuring and integrating Dialogflow ES with contact center platforms

Utilizing Dialogflow telephony integrations for voice-based interactions

Handling omnichannel conversations with Dialogflow integrations

Advanced Dialogflow Features for Contact Centers

Implementing sentiment analysis and sentiment-based responses

Building multi-turn conversations with dialog management and session entities

Utilizing Dialogflow’s analytics and insights for agent performance optimization

Testing, Deployment, and Continuous Improvement

Testing virtual agents using Dialogflow’s simulator and debugging tools

Deploying virtual agents in contact center environments

Monitoring and continuously improving virtual agent performance and user experience

Outcome

By the end of the CCAIDES course, participants will have:

• Developed a comprehensive understanding of conversational AI concepts and best practices in contact center environments
• Acquired practical knowledge in designing and developing virtual agents and chatbots using Dialogflow ES
• Gained expertise in natural language understanding, dialogue management, and integration with contact center platforms
• Learned techniques for testing, deployment, and continuous improvement of virtual agents
• Gained hands-on experience through practical labs and exercises
• Prepared to design and develop customer-centric conversational AI solutions using Dialogflow ES in contact center environments

Labs

The CCAIDES course includes hands-on labs that provide participants with practical experience in designing and developing conversational AI solutions using Dialogflow ES. Some examples of lab exercises include:

• Designing conversational flows and implementing intents, entities, and contexts in Dialogflow ES
• Implementing fulfillment and webhooks for enhancing virtual agent interactions
• Training and improving intent recognition models in Dialogflow ES
• Configuring Dialogflow telephony integrations for voice-based interactions
• Implementing sentiment analysis and sentiment-based responses in virtual agents
• Testing, deploying, and monitoring virtual agents in contact center environments

These labs enable participants to apply the concepts learned in the course and gain hands-on experience in designing and developing conversational AI solutions using Dialogflow ES, allowing them to develop practical skills in creating customer-centric experiences in contact centers.