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Duration 21 hours
Course Outline
Introduction to AI Assistants
- An overview of conversational AI and virtual assistant technologies.
- Current trends in AI-driven human-computer interaction.
- Key use cases across various industries.
Conversational AI Design and UI/UX
- Principles of human-centered design in AI.
- Constructing chatbot flows and mapping user interactions.
- Prototyping AI assistant interfaces using tools like Figma.
Natural Language Processing (NLP) and Context Awareness
- Exploring NLP models, including transformers, embeddings, and intent recognition.
- Techniques for entity extraction and context retention within conversations.
- Managing multi-turn dialogues and enhancing contextual understanding.
Building AI Assistants with Development Frameworks
- Selecting the appropriate development framework: Dialogflow, Rasa, or the OpenAI API.
- Implementing AI-driven dialogue flows.
- Integrating speech-to-text and text-to-speech capabilities.
Integrations and API Connectivity
- Connecting AI assistants to external APIs and databases.
- Integration with messaging platforms such as Slack and WhatsApp.
- Security best practices for AI-powered assistants.
Deployment and Maintenance
- Hosting AI assistants on cloud platforms.
- Monitoring and enhancing performance using 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.
- Working experience with at least one programming language, such as Python or JavaScript.
- Familiarity with UI/UX design principles (specifically for designers).
Target Audience
- AI developers.
- UI/UX designers.
- Professionals and enthusiasts in conversational AI.
