Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Conversational AI
- History and evolution of voice assistants
- Core components: Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Dialogue Management, and Text-to-Speech (TTS)
- Overview of major platforms: Alexa, Google Assistant, and Rasa
Designing Voice Interfaces
- Principles of conversational user experience (UX)
- Intent modeling and entity extraction
- Voice design tools and flowcharting techniques
Developing with Dialogflow and Alexa
- Dialogflow agents, intents, and webhook fulfillment
- Alexa Skills: intents, slots, voice models, and endpoint integration
- Managing multi-turn conversations and sessions
Building Voice Assistants with Rasa
- Rasa architecture: NLU, Core, and Actions
- Training data and domain configuration
- Implementing custom actions, forms, and contextual dialogues
Integrating Voice Assistants
- APIs and webhook backend services
- Connecting to CRMs, databases, and external applications
- Deploying voice assistants in web apps, IoT devices, and mobile platforms
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 compliance, and audit trails
- Version control and CI/CD pipelines for voice applications
Summary and Next Steps
Requirements
- Knowledge of RESTful APIs and JSON
- Experience with at least one programming language, such as Python or JavaScript
- Familiarity with natural language processing (NLP) concepts
Target Audience
- Software developers
- UX designers focusing on voice-based interfaces
- Conversational AI teams developing virtual assistants
21 Hours
