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Duration 21 hours
Course Outline
Introduction to AI Assistants
- Fundamentals of conversational AI and the role of virtual assistants
- Current trends in AI-enhanced human-computer interaction
- Key industry applications and use cases
Conversational AI Design and UI/UX
- Core principles of human-centered AI design
- Creating chatbot logic and mapping user interactions
- Prototyping AI assistant interfaces using Figma or similar tools
Natural Language Processing (NLP) and Context Awareness
- Exploring NLP models, including transformers, embeddings, and intent recognition
- Managing entity extraction and maintaining conversation context
- Addressing multi-turn dialogues and deep contextual understanding
Building AI Assistants with Development Frameworks
- Selecting the appropriate framework: Dialogflow, Rasa, or OpenAI API
- Developing AI-powered dialogue flows
- Incorporating speech-to-text and text-to-speech functionality
Integrations and API Connectivity
- Linking AI assistants to external APIs and databases
- Connecting with messaging platforms such as Slack and WhatsApp
- Implementing security best practices for AI-driven solutions
Deployment and Maintenance
- Hosting AI assistants on cloud infrastructure
- Tracking and enhancing performance through analytics
- Executing continuous model updates and fine-tuning strategies
Real-World Project Implementation
- Constructing a working AI assistant prototype
- Testing, debugging, and refining for actual users
- Final release and planning for future enhancements
Requirements
- A foundational grasp of artificial intelligence and machine learning concepts
- Practical experience with at least one programming language (e.g., Python, JavaScript, or similar)
- Knowledge of UI/UX design principles (essential for designers)
Target Audience
- AI developers
- UI/UX designers
- Professionals interested in conversational AI
