Get in Touch
 Duration 14 hours

Course Outline

Introduction to Edge AI

  • Core definitions and foundational concepts
  • Distinguishing features between Edge AI and Cloud AI
  • Advantages and potential obstacles of Edge AI
  • Survey of common Edge AI implementations

Edge AI Architecture

  • Essential components of Edge AI systems
  • Required hardware and software specifications
  • Data processing workflows in Edge AI contexts
  • Integrating Edge AI with established infrastructure

Setting Up the Edge AI Environment

  • Overview of key platforms (e.g., Raspberry Pi, NVIDIA Jetson)
  • Installing prerequisite software and libraries
  • Optimizing the development workspace configuration
  • Bootstrapping the Edge AI setup

Developing Edge AI Models

  • Review of machine learning and deep learning frameworks
  • Preparing models for edge-side execution
  • Techniques for model performance optimization
  • Essential tools and frameworks for Edge AI development

Deploying Edge AI Applications

  • Process for releasing models to edge hardware
  • Oversight and maintenance of live models
  • Handling real-time data streams and inference tasks
  • Analytical case studies and practical examples

Use Cases and Applications

  • Sector-specific Edge AI implementations
  • Case studies across healthcare, automotive, and smart home sectors
  • Insights from successful deployments and key takeaways
  • Emerging trends and future opportunities in Edge AI

Ethical Considerations and Best Practices

  • Safeguarding privacy and security in Edge AI systems
  • Mitigating bias and ensuring fairness in AI outcomes
  • Adhering to regulatory standards and compliance requirements
  • Standards for responsible and ethical AI deployment

Hands-On Projects and Exercises

  • Building a foundational Edge AI application
  • Tackling realistic professional scenarios and projects
  • Engaging in collaborative team-based exercises
  • Presenting projects and receiving structured feedback

Summary and Next Steps

Requirements

  • Foundational knowledge of AI and machine learning principles
  • Proficiency in programming languages (Python is preferred)
  • General awareness of computing fundamentals

Target Audience

  • Software Developers
  • IT Professionals

Number of participants


Price per participant (excl. VAT)

Testimonials (1)

Upcoming Courses

Related Categories