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Course Outline

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

Requirements

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

Target Audience

  • AI developers.
  • UI/UX designers.
  • Conversational AI enthusiasts.
 21 Hours

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