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Duration 21 hours
Course Outline
Introduction to AI Assistants
- Overview of conversational AI and the landscape of virtual assistants
- Emerging trends in AI-driven human-computer interaction
- Cross-industry use cases and applications
Conversational AI Design and UI/UX
- Core principles of human-centered AI design
- Constructing chatbot flows and mapping user interactions
- Prototyping AI assistant interfaces using Figma or comparable tools
Natural Language Processing (NLP) and Context Awareness
- Exploring NLP models, including transformers, embeddings, and intent recognition
- Entity extraction and maintaining context throughout conversations
- Managing multi-turn dialogues with deep contextual understanding
Building AI Assistants with Development Frameworks
- Selecting the appropriate development framework, such as Dialogflow, Rasa, or the OpenAI API
- Implementing intelligent, AI-driven dialogue structures
- Integrating speech-to-text and text-to-speech capabilities
Integrations and API Connectivity
- Connecting AI assistants to external APIs and database systems
- Integration with messaging platforms like Slack, WhatsApp, and others
- Implementing security best practices for AI-powered assistants
Deployment and Maintenance
- Hosting AI assistants on cloud infrastructure
- Monitoring and enhancing performance through data 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 user engagement
- Final deployment and planning for future enhancements
Requirements
- A foundational grasp of artificial intelligence and machine learning principles
- Proficiency in at least one programming language such as Python, JavaScript, or equivalent
- Working knowledge of UI/UX design fundamentals (specifically for designers)
Target Audience
- AI developers
- UI/UX designers
- Professionals interested in conversational AI
