Course Details
AI Chatbots Development - Programmer Track
This intensive workshop equips developers to design, build, and deploy AI chatbots for business applications. Participants will learn advanced programming techniques, including NLP, AI model integration, API connectivity, and multi-channel deployment, while building real-world projects for customer service, lead management, and internal automation. The workshop emphasizes hands-on experience with coding exercises, workflow integration, and performance analytics. Participants will also explore best practices for testing, optimization, and scaling chatbots, ensuring solutions are production-ready. By the end of the workshop, developers will gain the skills and confidence to deliver functional, intelligent chatbots that enhance customer engagement, automate workflows, and provide actionable business insights, ready to implement in their organization.
Learning Outcomes:
Course Outline:
Business value and use cases of AI chatbots
Types: rule-based vs AI/NLP chatbots
Architecture overview
Installing Python, Node.js, and development tools
Setting up chatbot frameworks (Dialogflow, Rasa, Microsoft Bot Framework)
OpenAI API and other NLP/AI model integration
Dialogue design principles
Intent, entity, and context management
Planning real-world chatbot project
Set up development environment and create first "Hello World" chatbot
Understanding tokenization, embeddings, and intent classification
Entity extraction and slot filling
Using GPT or custom LLMs for conversation
Implementing AI-generated responses
Prompt engineering best practices
Multi-turn conversations
Context handling and fallback strategies
Error recovery in chatbots
Build a chatbot that handles FAQs and multi-turn dialogues using AI
Connecting chatbots to backend systems, CRMs, and databases
Fetching and updating data in real-time
Handling authentication and secure access
Deploying chatbots on websites, WhatsApp, Messenger, Slack
Handling platform-specific limitations
Webhooks and real-time messaging
Automating lead qualification, ticketing, and notifications
Integrating with email, task, and support systems
Deploy a multi-channel chatbot integrated with a database and workflow automation
Chatbot KPIs: response time, resolution rate, engagement
Logging and tracking user interactions
Analyzing user feedback and chatbot performance
Fine-tuning intents and responses
Improving NLP model accuracy
Training chatbots from real-world conversation data
Data privacy, GDPR, and regulatory compliance
Secure handling of sensitive customer information
Implement analytics dashboard for chatbot performance
Optimize conversation flow using collected data
Plan, design, and develop a full chatbot for customer support or lead management
Integrate AI model, database, and multi-channel deployment
User testing, debugging, and performance improvements
Load testing and response optimization
Scaling chatbot for multiple users and platforms
Versioning, logging, and maintenance
Documentation for handover and continuous improvement
Deploy and demonstrate a fully functional AI chatbot
Present project and receive feedback
Prepare roadmap for workplace implementation
Review and discussion of tools and concepts covered.
Q&A session to address any questions.
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