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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
- Key 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 comparable tools
Natural Language Processing (NLP) and Context Awareness
- Understanding NLP models, including transformers, embeddings, and intent recognition
- Extracting entities and retaining context in conversations
- Managing multi-turn dialogues and ensuring contextual understanding
Building AI Assistants with Development Frameworks
- Selecting the appropriate development framework: Dialogflow, Rasa, or OpenAI API
- Implementing AI-driven dialogue flows
- Incorporating speech-to-text and text-to-speech capabilities
Integrations and API Connectivity
- Connecting AI assistants with external APIs and databases
- Integration with messaging platforms such as Slack and WhatsApp
- Applying security best practices for AI-powered assistants
Deployment and Maintenance
- Hosting AI assistants on cloud platforms
- 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 real users
- Final deployment and planning for future improvements
Requirements
- A foundational understanding of artificial intelligence and machine learning concepts.
- Proficiency in 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.
- Enthusiasts of conversational AI.
