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Duration 21 hours
Course Outline
Introduction to AI Assistants
- Overview of conversational AI and the landscape of virtual assistants.
- Current trends in AI-driven human-computer interaction.
- Key use cases across various industries.
Conversational AI Design and UI/UX
- Core principles of human-centered AI design.
- Developing chatbot flows and mapping user interactions.
- Prototyping AI assistant interfaces using Figma or equivalent tools.
Natural Language Processing (NLP) and Context Awareness
- Exploring NLP models, including transformers, embeddings, and intent recognition.
- Techniques for entity extraction and maintaining context in conversations.
- Managing multi-turn dialogues and ensuring contextual understanding.
Building AI Assistants with Development Frameworks
- Selecting the optimal development framework: Dialogflow, Rasa, or the OpenAI API.
- Implementing AI-driven dialogue flows.
- Incorporating speech-to-text and text-to-speech capabilities.
Integrations and API Connectivity
- Connecting AI assistants to external APIs and databases.
- Integrating with popular messaging platforms such as Slack and WhatsApp.
- Best practices for securing 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 enhancements.
Requirements
- A foundational understanding of artificial intelligence and machine learning concepts.
- Practical experience with at least one programming language, such as Python or JavaScript.
- A working knowledge of UI/UX design principles (essential for designers).
Target Audience
- AI developers.
- UI/UX designers.
- Professionals interested in conversational AI technologies.
