Course Outline

Introduction to Edge AI in Retail

  • Overview of Edge AI and its role in retail
  • Key benefits: low latency, real-time processing, and efficiency
  • Case studies of Edge AI applications in retail

Smart Checkout and Automated Payment Systems

  • AI-powered cashier-less checkout technologies
  • Object recognition for automatic billing
  • Customer authentication and fraud prevention

Inventory Management and Stock Optimization

  • Computer vision for shelf monitoring and restocking
  • Real-time demand forecasting with AI
  • RFID and IoT integration for automated tracking

Enhancing Customer Engagement with AI

  • Personalized recommendations using Edge AI
  • AI-powered virtual assistants in retail stores
  • Sentiment analysis and customer behavior tracking

Deploying and Managing Edge AI Solutions in Retail

  • Choosing the right hardware and software for Edge AI
  • Security and compliance considerations in retail AI
  • Scaling AI solutions across multiple store locations

Future Trends and Innovations in Edge AI for Retail

  • Advancements in AI-powered autonomous stores
  • Integrating Edge AI with augmented reality (AR) for shopping experiences
  • Ethical and regulatory considerations in AI-driven retail

Summary and Next Steps

Requirements

  • Basic understanding of AI and machine learning concepts
  • Familiarity with retail technology and automation
  • Experience with Python or AI frameworks is beneficial but not required

Audience

  • Retail technologists
  • AI developers
  • Business analysts
 21 Hours

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