Design Conversational AI Experience
What you'll learn
- You will be able to understand basic concepts behind Conversational AI system
- You will be able to understand various complexity levels associated with conversational AI
- You will be able to understand solution components of a Conversational AI system.
- You will be able to design a Conversational AI experience on a example self service use case
Requirements
- No
Description
During Covid-19 era, the emphasis on online customer engagement is rapidly increasing. Most organizations are already working on transforming their engagements to increase their online presence. Are you ready to transform your engagement to increase your online presence? Customer surveys find users are turned off from static web pages and drawn to messaging interfaces. How do you start defining a Conversational AI solution that goes beyond simple messaging?
This course will provide you with an appreciation for the complexity of conversational AI systems and desired components needed for a conversational engagement with your customers, suppliers and employees.
The course is divided into multiple sections and will cover many important aspects associated with Conversational AI, such as
We will cover key concepts behind Conversational AI , such as Listening and Comprehension, Knowledge of Subject area, Connect with User needs, Persuasion and Trusting relationship
We will cover the terms used in Conversational AI with illustrations. These includes - Utterances, Intents, Entities, Context, Dialog, Short-tail and Long-tail
We will psychological aspects of conversation. How do we improve the personality of an AI engine to better engage with its users?
We will ntroduce Conversational AI engines with classifications based on who is conversing and whether the AI engine is supporting or leading a conversation with its users.
We will provide a measure of the complexity of conversation. It uses the terms specified in previous sections and will illustrate how sophisticated Conversational AI systems can be build using advanced capabilities to improve user engagement.
We will various components of Conversational AI solution. It proposes an overall solution architecture that can be used to deploy the system in a real-life business process and used for collecting feedback, analyzing and enhancing its capabilities.
Finally, we will use design a conversation AI experience using the concepts defined in this course using an example self service use case.
Who this course is for:
- Customer engagement professionals Vendors, consultants and service providers
- Information technology management
- Senior year undergraduate and graduate students in Business & IT
- Vendors, consultants and service providers of AI technology
Course content
- Preview03:07
- 06:23Course Outline
- 1 questionPurpose of the course
Instructor
![Neena Sathi](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.2 Instructor Rating
- 89 Reviews
- 367 Students
- 11 Courses
Neena Sathi is a principal at Applied AI Institute. She has 30+ years of experience envisioning, designing, developing and implementing AI solutions associated with enhancing customer experience, back office automation and risk and compliance for many Fortune 100 organizations. She has worked in senior technical positions at Carnegie Group, Inc, an AI startup, Accenture, KPMG, and IBM.
Neena has three masters degrees including MBA from leading US universities. She is Master certified integration architect from IBM and Open Group as well as certified Project management professional (PMP) from Project management institute. She is also certified in many Cloud and Cognitive technologies. She has widely presented and published many papers in AAAI, IEEE, WCF, ECF, IBM Information on Demand, IBM Insight, World of Watson, IBM Developer Works and various academic journals.