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Duration 21 hours
Course Outline
Foundations of AI Assistants
- An overview of conversational AI and the role of virtual assistants
- Current trends in AI-driven human-computer interaction
- Key use cases spanning various industries
Designing Conversational AI and UI/UX
- Core principles of human-centered AI design
- Constructing chatbot flows and mapping user interactions
- Creating AI assistant interface prototypes using Figma or comparable tools
Natural Language Processing (NLP) and Context Awareness
- Exploring NLP models, including transformers, embeddings, and intent recognition
- Extracting entities and maintaining context throughout conversations
- Managing multi-turn dialogues with deep contextual understanding
Developing AI Assistants with Frameworks
- Selecting appropriate development frameworks such as Dialogflow, Rasa, or the OpenAI API
- Implementing AI-driven dialogue structures
- Incorporating speech-to-text and text-to-speech features
Integrations and API Connectivity
- Linking AI assistants with external APIs and database systems
- Integrating with popular messaging platforms like Slack and WhatsApp
- Applying security best practices for AI-powered assistants
Deployment and Maintenance
- Hosting AI assistants on cloud-based platforms
- Tracking and enhancing performance through analytics
- Executing ongoing model updates and fine-tuning strategies
Implementing Real-World Projects
- Constructing a functional AI assistant prototype
- Conducting testing, debugging, and optimization for real users
- Finalizing deployment and planning for future enhancements
Requirements
- A foundational grasp of artificial intelligence and machine learning concepts
- Proficiency in at least one programming language, such as Python, JavaScript, or similar
- An understanding of UI/UX design principles (specifically for designers)
Target Audience
- AI Developers
- UI/UX Designers
- Individuals passionate about Conversational AI
