Building AI Powered Chatbots Without Programming Course Syllabus

Overview (80-120 words) describing structure and time commitment.

Module 1: Introduction to AI Chatbots & Architecture

Estimated time: 1.5 hours

• Evolution of chatbots
• Large Language Model (LLM) basics
• AI chatbot system architecture
• Hands-on: Sketch a high-level architecture for an AI chatbot using GPT APIs

Module 2: Intent Recognition & Slot Filling

Estimated time: 2 hours

• Natural Language Understanding (NLU) concepts
• Training intent classifiers
• Entity extraction and slot filling
• Hands-on: Build and evaluate an intent classifier; implement slot-filling logic

Module 3: Conversational Flow Design

Estimated time: 2 hours

• Dialogue state management
• Designing decision trees for conversation paths
• Generative vs. rule-based dialogue approaches
• Hands-on: Create multi-turn flows with context variables in a chatbot framework

Module 4: Integrating LLMs into Your Bot

Estimated time: 2 hours

• Calling GPT/OpenAI APIs
• Prompt engineering techniques
• Handling and parsing API responses
• Hands-on: Implement a middleware that formats user inputs into prompts and parses outputs

Module 5: Rich Messaging & UI Components

Estimated time: 1.5 hours

• Designing interactive UI elements
• Using quick replies, buttons, and carousels
• Supporting images and multimedia responses
• Hands-on: Enhance your bot’s responses with interactive UI elements

Module 6: Multi-Channel Deployment

Estimated time: 2 hours

• Connecting to messaging platforms
• Deployment to Slack and WhatsApp
• Integrating web chat widgets
• Hands-on: Deploy your chatbot to Slack and test real-time interactions

Module 7: Testing, Analytics & Optimization

Estimated time: 1.5 hours

• Unit testing chatbot logic
• Conversational QA and user metrics tracking
• Running A/B tests on conversation flows
• Hands-on: Set up analytics dashboards and run a conversation-flow experiment

Module 8: Security, Privacy & Compliance

Estimated time: 1 hour

• Data handling best practices
• GDPR and CCPA compliance considerations
• Input sanitization and consent management
• Hands-on: Implement logging and consent management for user data

Prerequisites

• Familiarity with basic programming concepts
• Understanding of Python or JavaScript helpful but not required
• Access to OpenAI API key for lab exercises

What You'll Be Able to Do After

• Design effective conversational flows and user intents for AI-powered chatbots
• Integrate Large Language Models like OpenAI GPT into chatbot backends
• Implement rich messaging features such as buttons, carousels, and multimedia
• Deploy chatbots across web, mobile, and messaging platforms including Slack and WhatsApp
• Manage context, session data, and multi-turn conversations securely and efficiently