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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
- Diverse industry applications and use cases
Conversational AI Design 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 retaining context within dialogues
- Managing multi-turn conversations and deep contextual understanding
Developing AI Assistants with Frameworks
- Selecting the optimal development framework: Dialogflow, Rasa, or OpenAI API
- Implementing AI-guided dialogue structures
- Incorporating speech-to-text and text-to-speech functionalities
Integrations and API Connectivity
- Linking AI assistants with external APIs and database systems
- Connecting to messaging platforms like Slack, WhatsApp, and others
- Adopting security best practices for AI-driven solutions
Deployment and Maintenance
- Hosting AI assistants on various cloud platforms
- Monitoring and enhancing performance through analytics
- Implementing continuous model updates and fine-tuning methods
Real-World Project Implementation
- Constructing a working prototype of an AI assistant
- Testing, troubleshooting, and optimizing for end-users
- Final release preparation and strategies for future enhancements
Requirements
- A foundational grasp of artificial intelligence and machine learning principles.
- Proficiency in at least one programming language, such as Python, JavaScript, or a comparable tool.
- Knowledge of UI/UX design fundamentals (specifically for designers).
Target Audience
- AI Developers
- UI/UX Designers
- Enthusiasts of Conversational AI
