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Duration 21 hours
Course Outline
Fundamentals of AI Assistants
- An overview of conversational AI and the role of virtual assistants
- Current trends in AI-driven human-computer interaction
- Industry-specific use cases and applications
Conversational AI Architecture and UI/UX
- Core principles of human-centered AI design
- Developing chatbot flows and mapping user interactions
- Creating prototypes for AI assistant interfaces using Figma or comparable tools
Natural Language Processing (NLP) and Context Awareness
- Key components of NLP models, including transformers, embeddings, and intent recognition
- Techniques for entity extraction and maintaining conversational context
- Managing multi-turn dialogues and ensuring contextual understanding
Developing AI Assistants with Modern Frameworks
- Selecting appropriate development frameworks such as Dialogflow, Rasa, or the OpenAI API
- Building AI-powered dialogue flows
- Incorporating speech-to-text and text-to-speech features
System Integrations and API Connectivity
- Linking AI assistants to external APIs and databases
- Connecting with messaging platforms like Slack and WhatsApp
- Implementing security best practices for AI-driven systems
Deployment and Lifecycle Management
- Hosting AI assistants on cloud infrastructure
- Using analytics to monitor and enhance performance
- Strategies for continuous model updates and fine-tuning
Real-World Project Execution
- Constructing a working AI assistant prototype
- Conducting testing, debugging, and optimization for end-users
- Completing final deployment and planning future enhancements
Requirements
- A foundational grasp of artificial intelligence and machine learning principles
- Practical experience with at least one programming language such as Python, JavaScript, or similar
- A working knowledge of UI/UX design fundamentals (specifically for designers)
Target Audience
- AI developers
- UI/UX designers
- Professionals and enthusiasts interested in conversational AI
