Building Intelligent Voice Assistants with AI

• 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

Voice assistant platforms like Amazon Alexa, Google Dialogflow, and Rasa offer powerful frameworks for developing intelligent, voice-driven applications for both public and internal use cases.

This instructor-led, live training (online or onsite) is aimed at intermediate-level developers and design teams who wish to build, train, and deploy conversational voice interfaces that automate workflows and support users naturally via speech.

By the end of this training, participants will be able to:

• Design conversational flows and interaction models for voice UIs.
• Develop voice assistants using tools like Dialogflow, Alexa, and open-source frameworks such as Rasa.
• Integrate assistants with back-end APIs, databases, and third-party services.
• Deploy assistants to smart devices or web-based voice apps.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

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