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Duration 21 hours
Course Outline
Introduction to AI Assistants
- Overview of conversational AI and virtual assistants
- Current trends in AI-driven human-computer interaction
- Application cases across various industries
Conversational AI Design and UI/UX
- Core principles of human-centred AI design
- Developing chatbot flows and mapping user interactions
- Prototyping AI assistant interfaces using Figma or comparable tools
Natural Language Processing (NLP) and Context Awareness
- Comprehending NLP models (transformers, embeddings, intent recognition)
- Extracting entities and retaining context during conversations
- Managing multi-turn dialogues and deep contextual understanding
Building AI Assistants with Development Frameworks
- Selecting the appropriate development framework: Dialogflow, Rasa, or the OpenAI API
- Creating AI-driven dialogue structures
- Incorporating speech-to-text and text-to-speech functionality
Integrations and API Connectivity
- Linking AI assistants with external APIs and databases
- Integrating with messaging platforms (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
- Constructing a functional AI assistant prototype
- Testing, debugging, and optimising for end-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 coding language (such as Python, JavaScript, or similar)
- Knowledge of UI/UX design fundamentals (for designers)
Target Audience
- AI developers
- UI/UX designers
- Professionals interested in conversational AI
