Automate Interactions with Contact Center AI faq

learnersLearners: 23
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duration Duration: 8.00 duration-icon

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Course Feature Course Overview Course Provider Discussion and Reviews
Go to class

Course Feature

costCost:

Free

providerProvider:

Qwiklabs

certificateCertificate:

Free Certification

languageLanguage:

English

start dateStart Date:

On-Demand

Course Overview

❗The content presented here is sourced directly from Qwiklabs platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [May 19th, 2023]

This course provides an overview of the features of Contact Center AI, including how to build a virtual agent, design conversation flows, add a phone gateway, use Dialogflow for troubleshooting, and review logs and debug your virtual agent. Upon completion of the course, participants will receive a skill badge from Google Cloud in recognition of their proficiency with Google Cloud products and services. The course includes a quest and a final assessment challenge lab.

[Applications]
Upon completion of the Automate Interactions with Contact Center AI course, learners can apply their knowledge by building virtual agents, designing conversation flows, adding phone gateways, using Dialogflow for troubleshooting, and reviewing logs and debugging their virtual agents. Learners can also receive a skill badge from Google Cloud in recognition of their proficiency with Google Cloud products and services.

[Career Paths]
1. AI Engineer: AI Engineers are responsible for developing and deploying AI solutions. They design, build, and maintain AI systems, and use machine learning algorithms to create models that can be used to automate tasks. AI Engineers must have a strong understanding of programming languages, such as Python, and be able to work with large datasets. AI Engineers are in high demand, and the demand is expected to continue to grow as AI technology advances.

2. Machine Learning Engineer: Machine Learning Engineers are responsible for developing and deploying machine learning models. They design, build, and maintain machine learning systems, and use algorithms to create models that can be used to automate tasks. Machine Learning Engineers must have a strong understanding of programming languages, such as Python, and be able to work with large datasets. Machine Learning Engineers are in high demand, and the demand is expected to continue to grow as machine learning technology advances.

3. Data Scientist: Data Scientists are responsible for analyzing and interpreting data. They use statistical methods and machine learning algorithms to uncover insights from data. Data Scientists must have a strong understanding of programming languages, such as Python, and be able to work with large datasets. Data Scientists are in high demand, and the demand is expected to continue to grow as data science technology advances.

4. Natural Language Processing Engineer: Natural Language Processing Engineers are responsible for developing and deploying natural language processing (NLP) solutions. They design, build, and maintain NLP systems, and use algorithms to create models that can be used to automate tasks. Natural Language Processing Engineers must have a strong understanding of programming languages, such as Python, and be able to work with large datasets. Natural Language Processing Engineers are in high demand, and the demand is expected to continue to grow as NLP technology advances.

[Education Paths]
1. Bachelor of Science in Artificial Intelligence: A Bachelor of Science in Artificial Intelligence is a four-year degree program that focuses on the development of computer systems that can think and learn. Students learn about the fundamentals of AI, including machine learning, natural language processing, and robotics. This degree is becoming increasingly popular as AI technology continues to develop and become more widely used.

2. Master of Science in Machine Learning: A Master of Science in Machine Learning is a two-year degree program that focuses on the development of algorithms and models that can learn from data. Students learn about the fundamentals of machine learning, including supervised and unsupervised learning, deep learning, and reinforcement learning. This degree is becoming increasingly popular as machine learning technology continues to develop and become more widely used.

3. Doctor of Philosophy in Computer Science: A Doctor of Philosophy in Computer Science is a four-year degree program that focuses on the development of computer systems that can think and learn. Students learn about the fundamentals of AI, including machine learning, natural language processing, and robotics. This degree is becoming increasingly popular as AI technology continues to develop and become more widely used.

4. Master of Science in Data Science: A Master of Science in Data Science is a two-year degree program that focuses on the development of algorithms and models that can learn from data. Students learn about the fundamentals of data science, including data mining, data visualization, and predictive analytics. This degree is becoming increasingly popular as data science technology continues to develop and become more widely used.

Course Syllabus

How does Google Cloud Contact Center AI work?

Design Conversational Flows for your Agent

Contact Center AI can increase customer satisfaction and operational efficiency by improving call deflection rates, and achieve shorter handling, while making overall operations faster and more effective. In this lab, you'll learn how to use Dialogflow to create a conversational interface.

Building Virtual Agent Fulfillment

In this lab, you will continue working on your Pigeon Travel chat agent and add context as well as setup fulfillment to lookup and store reservations entries in Firestore.

Adding a Phone Gateway to a Virtual Agent

In this lab you will continue working on your Pigeon Travel virtual agent and add a phone gateway to allow users to call into your virtual agent.

Dialogflow Logging and Monitoring in Operations Suite

In this lab you will learn how to use Dialogflow tools to troubleshoot your Virtual Agent.

Automate Interactions with Contact Center AI: Challenge Lab

Configure and deploy the Speech Analysis Framework and be able to leverage BigQuery for insights on data extracted from call recordings on a call center environment.

Course Provider

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faq FAQ for Google Cloud Platform (GCP) Courses

Q1: Does the course offer certificates upon completion?

Yes, this course offers a free certificate. AZ Class have already checked the course certification options for you. Access the class for more details.

Q2: How do I contact your customer support team for more information?

If you have questions about the course content or need help, you can contact us through "Contact Us" at the bottom of the page.

Q3: Can I take this course for free?

Yes, this is a free course offered by Qwiklabs, please click the "go to class" button to access more details.

Q4: How many people have enrolled in this course?

So far, a total of 23 people have participated in this course. The duration of this course is 8.00 hour(s). Please arrange it according to your own time.

Q5: How Do I Enroll in This Course?

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