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Course Outline
Introduction to Conversational AI
- The historical progression and evolution of voice assistants.
- Core components: ASR, NLU, Dialogue Management, and TTS.
- An overview of key platforms including Alexa, Google Assistant, and Rasa.
Crafting Voice Interfaces
- Fundamental principles of conversational UX.
- Modeling intents and extracting entities.
Development with Dialogflow and Alexa
- Managing multi-turn conversations and session states.
Building Assistants with Rasa
- Rasa architecture: NLU, Core, and Action modules.
- Configuration of training data and domains.
- Implementing custom actions, forms, and contextual dialogues.
Integration Strategies
- Connecting APIs and webhook back-end services.
Testing, Deployment, and Performance
- Utilizing simulators and test cases for voice interactions.
- Monitoring usage patterns and debugging conversation flows.
Security, Compliance, and Scaling
Wrap-up and Future Directions
Requirements
- Proficiency in RESTful APIs and JSON structures.
- Working knowledge of at least one programming language, such as Python or JavaScript.
- Foundational understanding of natural language processing concepts.
Target Audience
- Software engineers.
- UX designers specializing in voice interfaces.
- Conversational AI teams focused on virtual assistant development.
21 Hours
