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Duration 21 hours (3 days)
Course Outline
Introduction to Conversational AI
- The historical development and evolution of voice assistants
- Essential components: ASR, NLU, Dialogue Management, and TTS
- A look at leading platforms: Alexa, Google Assistant, and Rasa
Designing Voice Interfaces
- Core principles of conversational user experience
- Modeling intents and extracting entities
- Utilizing voice design tools and flowcharting techniques
Development with Dialogflow and Alexa
- Managing Dialogflow agents, intents, and webhook fulfillment
- Creating Alexa Skills: handling intents, slots, voice models, and endpoint integration
- Handling multi-turn conversations and session state management
Constructing Voice Assistants with Rasa
- Understanding Rasa architecture: NLU, Core, and Actions
- Configuring training data and domain definitions
- Implementing custom actions, forms, and contextual dialogues
Integrating Voice Assistants
- Connecting to APIs and back-end webhook services
- Linking with CRMs, databases, and external applications
- Deploying voice assistants in web apps, IoT environments, and mobile platforms
Testing, Deployment, and Optimization
- Using simulators and test cases to validate voice interactions
- Monitoring usage patterns and debugging conversation flows
- Launching to Google Assistant, Alexa devices, or proprietary platforms
Security, Compliance, and Scalability
- Implementing user authentication and authorization for assistants
- Ensuring data privacy, GDPR compliance, and maintaining audit trails
- Managing version control and CI/CD pipelines for voice applications
Summary and Future Directions
Requirements
- Proficiency in RESTful APIs and JSON structures
- Practical experience with at least one programming language (such as Python or JavaScript)
- Foundational knowledge of natural language processing principles
Target Audience
- Software engineers
- UX designers focused on voice-based interaction design
- Conversational AI teams developing virtual assistants