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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

  • Fundamental understanding of AI and machine learning concepts.
  • Familiarity with retail technology and automation.
  • Experience with Python or AI frameworks is advantageous but not mandatory.

Audience

  • Retail technologists.
  • AI developers.
  • Business analysts.
 21 Hours

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