Description

Introduction

The Conversational AI Development Bootcamp is designed to equip learners with hands-on knowledge of designing, developing, and deploying intelligent virtual assistants using cutting-edge AI and natural language processing (NLP) tools. Whether you’re building customer service bots, virtual companions, or voice-based assistants, this bootcamp takes you from foundational concepts to real-world applications using platforms like Rasa, Dialogflow, and Large Language Models (LLMs).

Prerequisites

• Basic programming knowledge (Python preferred)

• Familiarity with REST APIs and JSON

• Understanding of how web applications work

• Interest in AI, machine learning, or chatbot development

Table of Contents

1. Foundations of Conversational AI
    1.1 What is Conversational AI?
    1.2 Evolution and Use Cases
    1.3 Rule-Based vs. AI-Based Bots

2. Natural Language Processing (NLP) Essentials
    2.1 Tokenization, Lemmatization, Intent Classification
    2.2 Entity Recognition and Dialogue Flow
    2.3 Popular NLP Libraries (spaCy, NLTK)

3. Working with Dialogflow
    3.1 Creating Agents, Intents, and Entities
    3.2 Context Handling and Webhook Integration
    3.3 Fulfillment and External API Calls
    3.4 Deployment to Web and Messaging Platforms

4. Building AI Bots with Rasa
    4.1 Installing and Setting up Rasa Stack
    4.2 Training NLU and Dialogue Models
    4.3 Custom Actions with Python
    4.4 Using Rasa X for Testing and Collaboration

5. Voice Interfaces and Assistants
    5.1 Introduction to Voice AI
    5.2 Integrating with Google Assistant or Alexa
    5.3 Text-to-Speech and Speech Recognition Basics

6. Large Language Models in Chatbots
    6.1 Introduction to ChatGPT, LLaMA, and Claude
    6.2 Fine-tuning and Prompt Engineering Basics
    6.3 Embedding LLMs in Custom Applications

7. Bot Integration and Deployment
    7.1 Frontend & Backend Integration
    7.2 Deploying Bots to Slack, WhatsApp, and Websites
    7.3 Hosting on Cloud Platforms (GCP, AWS, Azure)

8. Monitoring, Analytics & Logging
    8.1 Tracking User Interactions
    8.2 Logging and Error Monitoring
    8.3 Metrics for Bot Performance (F-score, Retention)

9. Security and Compliance in AI Bots
    9.1 Data Privacy Best Practices
    9.2 Role-Based Access and Authentication
    9.3 Compliance with GDPR and other Standards

10. Capstone Project & Real-World Scenarios
     10.1 Planning and Designing a Conversational Agent
     10.2 Development Sprint
     10.3 Testing and Feedback
     10.4 Final Presentation and Evaluation

Conclusion

By the end of this bootcamp, participants will be able to build, train, and deploy production-ready conversational AI systems using modern tools and frameworks. With a deep understanding of NLP, machine learning, and chatbot architecture, learners are prepared to apply their skills across industries from customer service to healthcare and beyond.