Next-Gen AI Assistants: From Design to Deployment

• Basic understanding of artificial intelligence and machine learning concepts
• Experience with at least one programming language (Python, JavaScript, or similar)
• Familiarity with UI/UX design principles (for designers)

Audience

• AI developers
• UI/UX designers
• Conversational AI enthusiasts

Next-Gen AI Assistants are intelligent, conversational, and context-aware virtual assistants that leverage NLP, multimodal AI, and advanced design principles to provide seamless user interactions.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level AI developers and UI/UX designers who wish to learn how to build, optimize, and deploy AI-powered virtual assistants.

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

• Design effective conversational AI workflows and UI/UX interfaces.
• Implement AI-driven natural language processing (NLP) models.
• Integrate AI assistants with APIs and third-party platforms.
• Deploy and maintain AI assistants for real-world applications.

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 AI Assistants

• Overview of conversational AI and virtual assistants
• Trends in AI-driven human-computer interaction
• Use cases across industries

Conversational AI Design and UI/UX

• Principles of human-centered AI design
• Building chatbot flows and user interaction mapping
• Prototyping AI assistant interfaces using Figma or similar tools

Natural Language Processing (NLP) and Context Awareness

• Understanding NLP models (transformers, embeddings, intent recognition)
• Entity extraction and context retention in conversations
• Handling multi-turn dialogues and contextual understanding

Building AI Assistants with Development Frameworks

• Choosing the right development framework: Dialogflow, Rasa, OpenAI API
• Implementing AI-driven dialogue flows
• Integrating speech-to-text and text-to-speech capabilities

Integrations and API Connectivity

• Connecting AI assistants with external APIs and databases
• Integrating with messaging platforms (Slack, WhatsApp, etc.)
• Security best practices for AI-powered assistants

Deployment and Maintenance

• Hosting AI assistants on cloud platforms
• Monitoring and improving performance with analytics
• Ongoing model updates and fine-tuning strategies

Real-World Project Implementation

• Building a functional AI assistant prototype
• Testing, debugging, and optimizing for real users
• Final deployment and future improvements

Summary and Next Steps