Course Modules

A structured learning path from fundamentals to mastery in conversational AI design and implementation.

01

Introduction to Conversational AI

Explore the fundamentals of chatbots, voice assistants, and the evolution of conversational interfaces.

Chatbots Voice Assistants IVR Systems Use Cases
02

Basics of Natural Language Processing

Learn about NLP, NLU, NLG, tokenization, intent recognition, and entity extraction.

NLP Intent Recognition Entity Extraction Sentiment Analysis
03

Getting Started with Amazon Lex

Build your first Lex bot with intents, slots, prompts, and Lambda integration.

Lex Console Intents Slots Lambda
04

Designing Conversational Flows

Master dialogue management, context handling, and designing for error recovery.

Dialogue Management Context Conditional Logic Error Recovery
05

Enhancing Bots with Advanced NLP & LLMs

Integrate OpenAI models, implement few-shot prompting, and handle ambiguity.

OpenAI Few-Shot Prompting RAG Ambiguity
06

Deployment & Scaling

Connect to channels, implement backend logic, and optimize for performance and cost.

Channels Lambda API Gateway Monitoring
07

Improving Bot Performance

Optimize training data, implement A/B testing, and create feedback loops.

Training Data A/B Testing Feedback Loops Kendra
08

Ethics & Security in Conversational AI

Address bias, ensure privacy compliance, and implement secure authentication.

Bias Mitigation Privacy GDPR Authentication
09

Beyond Lex: Hybrid Approaches

Explore combinations with other platforms, custom ML models, and voice assistants.

Hybrid Systems Custom ML Voice Assistants Multimodal
10

Capstone Project & Next Steps

Apply your knowledge to build a complete conversational AI project.

Project Planning Implementation Testing Documentation

Recommended Learning Path

Beginner

Start here if you're new to conversational AI

Advanced

Master advanced concepts and techniques

Capstone

Apply everything you've learned

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