
This is an introductory lecture on Conversational AI
In this lecture, we will see what all AWS Services are required for building a chat or voice bot. The services include:
Lex
Lambda
Polly
EC2
Cloudwatch
DynamoDB
Cognito
IAM
While there are many other services which can be used, these are most common ones.
Build a customer support bot using AWS services by wiring Cognito, Lambda, and Lex, configure channels and language settings, and monitor with CloudWatch logs.
Explore natural language understanding and processing with AWS Lex, covering intent classification, entity extraction, sentiment analysis, context handling, and natural language generation.
Apply design principles and composition design to craft enterprise bot conversations, guiding dialogue, context, and follow-up for clear, focused interactions.
Explore the conversation design process for enterprise bots by defining language for conversations, gathering use cases and user stories, creating dialogues, and testing via simulations to optimize long-term bot performance.
Explore style guide and conversation components for enterprise bots, mastering tone, contractions, and natural responses to design effective, user-friendly AWS Lex bots.
Demonstrate an appointment bot conversation flow for healthcare, from patient registration to booking, across hospital websites and WhatsApp, with prompts, doctor selection, and emergency handling.
Explore identifying intents and entities from conversation flow and chaining intents to support an appointment booking flow, including doctor search, insurance search, and collecting patient details.
Learn to design and build a Lex bot with conversation flows, intents, slots, and confirmations, and connect its fulfillment to back-end business logic.
Discover how the state object drives conversational flow in AWS Lex bots, detailing the dialogue state, elicited slots, and confirmation to fulfillment in a doctor appointment workflow.
Implement the standard flow in AWS Lex by wiring location, doctor, and date slots, adding validation, eliciting prompts, and using response cards to guide conversations.
Learn how session attributes enable context management in AWS Lex, carry slot data like user name across intents, and personalize interactions in a book-appointment flow across web channels.
Explore how intent chaining links book appointment and registration intents in AWS Lex, using phone number validation, conditional routing, and context management to guide users back to the correct flow.
Publish the enterprise bot to channels such as Facebook Messenger and Slack by establishing channel connections, then publish a version to an alias and test interactions with fallbacks and validations.
As a part of the course, you will learn the entire life cycle of developing an enterprise-grade virtual assistant. Starting from information gathering, conversation design, language model development, and developing the business logic. You will also get a clear idea of the AWS services like AWS Lex and Lambda. This is going to be more of hands-on and practical experience. The focus is on the core concepts of developing virtual assistants.
At the end of every section, you see quizzes and activities to help you internalize the concepts to the core. At the end of the course, you have one practical exam to test your overall learnings. This course is packed with value. Artificial Intelligence is in great demand today. This is the best course you need to give a kick start to your career as a conversational AI specialist. I am really excited to be part of your conversational AI journey. Welcome to this course.