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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
- Use cases across various industries
Conversational AI Design and UI/UX
- Principles of human-centered AI design
- Constructing chatbot flows and mapping user interactions
- Prototyping AI assistant interfaces using Figma or similar tools
Natural Language Processing (NLP) and Context Awareness
- Understanding NLP models (transformers, embeddings, intent recognition)
- Entity extraction and maintaining context in conversations
- Managing multi-turn dialogues and contextual understanding
Building AI Assistants with Development Frameworks
- Selecting the appropriate development framework: Dialogflow, Rasa, OpenAI API
- Implementing AI-driven dialogue flows
- Integrating speech-to-text and text-to-speech capabilities
Integrations and API Connectivity
- Connecting AI assistants with external APIs and databases
- Integrating with messaging platforms (Slack, WhatsApp, etc.)
- Best practices for security in AI-powered assistants
Deployment and Maintenance
- Hosting AI assistants on cloud platforms
- Monitoring and enhancing performance through analytics
- Ongoing model updates and fine-tuning strategies
Real-World Project Implementation
- Developing a functional AI assistant prototype
- Testing, debugging, and optimizing for actual users
- Final deployment and planning for future improvements
Requirements
- A foundational understanding of artificial intelligence and machine learning concepts
- Experience with at least one programming language (such as Python, JavaScript, or similar)
- Familiarity with UI/UX design principles (for designers)
Audience
- AI developers
- UI/UX designers
- Conversational AI enthusiasts
