Edge Computing Training Course

This advanced course delves into the innovative realm of edge computing, providing a comprehensive exploration of sophisticated architectures and addressing integration challenges. Participants will gain the necessary skills to leverage the full potential of edge computing in various government environments. The curriculum focuses on developing expertise in cutting-edge tools and methodologies to deploy, manage, and optimize edge computing solutions that meet specific public sector needs for government.

This instructor-led, live training in US (online or onsite) is designed for intermediate-level IT professionals and business managers who seek to understand the potential of IoT and edge computing for enhancing efficiency, enabling real-time processing, and fostering innovation across various industries.

By the end of this training, participants will be able to:

• Comprehend the principles of IoT and edge computing and their significance in digital transformation for government and private sectors.
• Identify use cases for IoT and edge computing in manufacturing, logistics, and energy sectors, including applications for government operations.
• Differentiate between edge and cloud computing architectures and deployment scenarios suitable for government and enterprise environments.
• Implement edge computing solutions to support predictive maintenance and real-time decision-making in both public and private sector contexts.

This comprehensive course integrates the transformative power of artificial intelligence (AI) with the agility of edge computing. Participants will learn to deploy AI models directly on edge devices, covering topics from understanding convolutional neural network (CNN) architectures to mastering knowledge distillation and federated learning. This hands-on training is designed to equip professionals with the skills necessary to optimize AI performance for real-time processing and decision-making at the edge, ensuring alignment with public sector workflows and governance for government applications.

This instructor-led, live training (online or onsite) is designed for intermediate-level developers, system architects, and industry professionals who aim to leverage Edge AI to enhance IoT applications with advanced data processing and analytics capabilities.

By the end of this training, participants will be able to:

• Comprehend the core principles of Edge AI and its application in IoT systems.
• Establish and configure Edge AI environments for IoT devices.
• Create and deploy AI models on edge devices to support IoT applications.
• Execute real-time data processing and decision-making within IoT frameworks.
• Integrate Edge AI with a variety of IoT protocols and platforms.
• Address ethical considerations and best practices in the deployment of Edge AI for government and industry use cases.

Establish a robust foundation in designing and managing a resilient edge computing infrastructure for government. Gain insights into open hybrid cloud infrastructures, the management of workloads across multiple clouds, and the importance of flexibility and redundancy. This training offers critical knowledge on developing a scalable and secure infrastructure that supports the evolving needs of modern applications through edge computing.

This instructor-led, live training (available online or onsite) is designed for intermediate-level professionals who wish to apply Federated Learning to enhance IoT and edge computing solutions for government. By the end of this training, participants will be able to: - Understand the principles and benefits of Federated Learning in IoT and edge computing environments. - Implement Federated Learning models on IoT devices to enable decentralized AI processing. - Reduce latency and improve real-time decision-making capabilities in edge computing scenarios. - Address challenges related to data privacy and network constraints in government IoT systems.