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Course Outline

Introduction to Edge AI

  • Core definitions and key principles
  • Comparing Edge AI with Cloud-based AI
  • Advantages and obstacles associated with Edge AI
  • An overview of typical Edge AI uses

Edge AI Frameworks

  • Key elements of Edge AI systems
  • Necessary hardware and software specifications
  • Data movement within Edge AI contexts
  • Connecting with current infrastructure

Preparing the Edge AI Workspace

  • Exploring Edge AI platforms (such as Raspberry Pi and NVIDIA Jetson)
  • Setting up essential software and libraries
  • Adjusting the development setup
  • Starting the Edge AI configuration process

Building Edge AI Models

  • Overview of machine learning and deep learning structures
  • Preparing models for peripheral device integration
  • Strategies for optimizing model performance
  • Essential tools and frameworks for Edge AI creation

Rolling Out Edge AI Solutions

  • Procedures for installing models on peripheral devices
  • Overseeing and managing live models
  • Instant data analysis and inference processes
  • Real-world examples and detailed scenarios

Practical Applications

  • Sector-specific implementations of Edge AI
  • Detailed studies in medical, automotive, and residential tech fields
  • Successful case studies and key takeaways
  • Emerging trends and future potential in Edge AI

Ethical Guidelines and Standards

  • Safeguarding privacy and security in Edge AI contexts
  • Mitigating bias and ensuring equity
  • Adhering to legal regulations and industry standards
  • Best methods for deploying AI responsibly

Practical Projects and Drills

  • Creating a basic Edge AI solution
  • Working on realistic, industry-relevant projects
  • Team-based collaborative activities
  • Presenting projects and receiving constructive feedback

Recap and Future Directions

Requirements

  • A foundational grasp of core AI and machine learning principles
  • Proficiency in programming languages (Python is preferred)
  • General knowledge of computing fundamentals

Target Learners

  • Software Developers
  • IT Specialists
 14 Hours

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