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Kursplan
Introduction to Conversational AI
- History and evolution of voice assistants
- Key components: ASR, NLU, Dialogue Management, TTS
- Overview of major platforms: Alexa, Google Assistant, Rasa
Designing Voice Interfaces
- Principles of conversational UX
- Intent modeling and entity extraction
- Voice design tools and flowcharting
Developing with Dialogflow and Alexa
- Dialogflow agents, intents, and webhook fulfillment
- Alexa Skills: intents, slots, voice models, and endpoint integration
- Multi-turn conversations and session management
Building Voice Assistants with Rasa
- Rasa architecture: NLU, Core, and Actions
- Training data and domain configuration
- Custom actions, forms, and contextual dialogues
Integrating Voice Assistants
- APIs and webhook back-end services
- Connecting to CRMs, databases, and external apps
- Voice assistants in web apps, IoT, and mobile
Testing, Deployment, and Optimization
- Simulators and test cases for voice interactions
- Monitoring usage and debugging conversations
- Deploying to Google Assistant, Alexa devices, or private platforms
Security, Compliance, and Scalability
- User authentication and authorization for assistants
- Data privacy, GDPR, and audit trails
- Version control and CI/CD pipelines for voice apps
Summary and Next Steps
Krav
- An understanding of RESTful APIs and JSON
- Experience with at least one programming language (e.g., Python or JavaScript)
- Familiarity with natural language processing concepts
Audience
- Software developers
- UX designers working on voice-based interfaces
- Conversational AI teams building virtual assistants
21 timer
