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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-enhanced human-computer interaction
- Key applications across various industries
Conversational AI Design and UI/UX
- Core principles of human-centered AI design
- Developing chatbot logic and mapping user interactions
- Creating prototypes for AI assistant interfaces 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 within conversations
- Managing multi-turn dialogues and deep contextual understanding
Building AI Assistants with Development 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 functionalities
Integrations and API Connectivity
- Linking AI assistants to external APIs and databases
- Connecting with popular messaging platforms like Slack and WhatsApp
- Applying security best practices for AI-driven systems
Deployment and Maintenance
- Hosting AI assistants on cloud infrastructure
- Tracking and enhancing performance through analytics
- Executing ongoing model updates and fine-tuning strategies
Real-World Project Implementation
- Constructing a working AI assistant prototype
- Conducting testing, debugging, and optimization for end users
- Completing final deployment and planning future enhancements
Requirements
- Fundamental knowledge of artificial intelligence and machine learning concepts
- Practical experience with at least one programming language, such as Python or JavaScript
- Acquaintance with UI/UX design principles (specifically relevant for designers)
Target Audience
- AI developers
- UI/UX designers
- Enthusiasts of conversational AI
