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Duration 35 hours
Course Outline
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Foundations of Edge AI for Government Applications
- Defining Edge AI and its strategic importance in public sector operations
- Advantages of implementing AI models at the network edge for government
- Survey of the current AI ecosystem supporting edge computing
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Convolutional Neural Network (CNN) Architectures in Edge Contexts
- Fundamentals of CNNs and their relevance to Edge AI frameworks
- Architectural considerations for deploying CNNs on constrained edge devices
- Analysis of case studies featuring efficient CNN implementations
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Designing Compact Networks for Edge Integration
- Methodologies for minimizing model footprint while maintaining precision
- Utilizing specialized tools and frameworks for model refinement
- Assessing the balance between computational performance and model complexity
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Knowledge Distillation Techniques for Edge AI
- Core principles of knowledge distillation and associated operational benefits
- Procedures for applying knowledge distillation to edge-based models
- Review of practical applications and documented success outcomes
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Advanced Compression Methods for Edge AI Models
- Examination of model compression strategies, including pruning and quantization
- Integration of compression techniques into edge AI operational scenarios
- Evaluation of effects on system performance, accuracy, and deployment logistics
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Federated Learning Principles and Practical Uses
- Overview of federated learning and its role in safeguarding privacy and efficiency
- Structural and functional components of federated learning architectures
- Addressing challenges and implementing solutions for edge-based federated learning
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Execution of Edge AI Solutions
- Complete workflow for deploying AI models on edge infrastructure
- Review of platforms and tools that facilitate Edge AI development
- Oversight and maintenance of Edge AI applications in live environments
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Case Analyses and Applied Projects
- Evaluation of real-world Edge AI implementations across multiple domains
- Collaborative project: Engineering and execution of an Edge AI solution
- Delivery and professional review of project deliverables
Requirements
- Proficiency in cloud computing and artificial intelligence concepts
Intended Audience
- Business Analysts
- Product Managers
- Developers
Testimonials (1)
That we can cover advance topic and work with real-life example
