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Duration 21 hours
Course Outline
Foundations of AI Assistants
- An introduction to conversational AI and the role of virtual assistants
- Current trends in AI-driven human-computer interaction
- Key use cases across various industries
Designing Conversational AI and UI/UX
- Core principles of human-centered AI design
- Developing chatbot flows and mapping user interactions
- Creating prototypes for AI assistant interfaces using tools like Figma or similar
Natural Language Processing (NLP) and Contextual Awareness
- Exploring NLP architectures including transformers, embeddings, and intent recognition
- Techniques for entity extraction and retaining context during conversations
- Managing multi-turn dialogues and achieving deeper contextual understanding
Developing AI Assistants with Modern Frameworks
- Selecting appropriate development frameworks such as Dialogflow, Rasa, or the OpenAI API
- Implementing intelligent, AI-driven dialogue structures
- Incorporating speech-to-text and text-to-speech functionalities
API Integrations and Connectivity
- Linking AI assistants with external APIs and database systems
- Integration with popular messaging platforms like Slack, WhatsApp, and others
- Adopting security best practices for AI-powered solutions
Deployment and Ongoing Maintenance
- Hosting AI assistants on scalable cloud platforms
- Tracking and enhancing performance through data analytics
- Strategies for continuous model updates and fine-tuning
Applying Skills to Real-World Projects
- Constructing a fully functional AI assistant prototype
- Conducting testing, debugging, and optimization for end-users
- Finalizing deployment and planning for future enhancements
Requirements
- Fundamental knowledge of artificial intelligence and machine learning concepts
- Proficiency in at least one programming language, such as Python, JavaScript, or equivalent
- A solid grasp of UI/UX design principles (specifically for designers)
Target Audience
- AI developers
- UI/UX designers
- Professionals interested in conversational AI