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Duration 21 hours
Course Outline
Introduction to AI Assistants
- Overview of conversational AI and virtual assistants
- Emerging trends in AI-driven human-computer interaction
- Industry-specific use cases
Conversational AI Design and UI/UX
- Core principles of human-centered AI design
- Creating chatbot flows and mapping user interactions
- Prototyping AI assistant interfaces with Figma or comparable tools
Natural Language Processing (NLP) and Context Awareness
- Comprehending NLP models (including transformers, embeddings, and intent recognition)
- Entity extraction and context retention during conversations
- Managing multi-turn dialogues and enhancing contextual understanding
Building AI Assistants with Development Frameworks
- Selecting appropriate development frameworks: Dialogflow, Rasa, or OpenAI API
- Implementing AI-driven dialogue flows
- Incorporating speech-to-text and text-to-speech functionalities
Integrations and API Connectivity
- Linking AI assistants with external APIs and databases
- Integration with messaging platforms (such as Slack, WhatsApp, etc.)
- Security best practices for AI-powered assistants
Deployment and Maintenance
- Hosting AI assistants on cloud infrastructure
- Monitoring and enhancing performance through analytics
- Strategies for ongoing model updates and fine-tuning
Real-World Project Implementation
- Developing a functional AI assistant prototype
- Testing, debugging, and optimizing for actual users
- Final deployment and planning for future enhancements
Requirements
- A foundational grasp of artificial intelligence and machine learning principles
- Practical experience with at least one programming language (such as Python, JavaScript, or similar)
- Knowledge of UI/UX design principles (specifically for designers)
Target Audience
- AI developers
- UI/UX designers
- Individuals passionate about Conversational AI
