Online or onsite, instructor-led live Edge Computing training courses demonstrate through interactive hands-on practice how to use Edge Computing to decentralize data management for faster performance, leveraging smart devices located on the source network.
Edge Computing training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Edge Computing trainings in Recife can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Recife - JCPM Trade Center
60 Eng. Antonio de Goes Avenue, 7º and 14º floor, , Recife, Brazil, 51010-000
The Recife JCPM Trade Center is in a 20-story building. The center has access to a helipad and five floors of parking. It is 10km from Guararapas International Airport.
Recife-Cicero Dias Shopping Center Recife
Rua Padre Carapuceiro, 858 , Recife, Brazil, 51020-280
The business center is located in the Cicero Dias Tower, part of a prestigious complex of five buildings, the Queiroz Galvão Center. Its stands out for its distinctive architecture and for being located in an area with a consolidated entrepreneurial vocation. The business center has a privileged position in Pernambuco, in one of the greatest development axis of northeastern Brazil. The business center is walking distance to one of the Recife's greatest shopping centers and from Shopping subway station. It is also 30 minutes away from the Port of Suape, one of the most important seaports in the country and a 7-minute drive from Guararapes International Airport.
This instructor-led, live training in Recife (online or onsite) is aimed at intermediate-level professionals who wish to apply Federated Learning to optimize IoT and edge computing solutions.
By the end of this training, participants will be able to:
Understand the principles and benefits of Federated Learning in IoT and edge computing.
Implement Federated Learning models on IoT devices for decentralized AI processing.
Reduce latency and improve real-time decision-making in edge computing environments.
Address challenges related to data privacy and network constraints in IoT systems.
This instructor-led, live training in Recife (online or onsite) is aimed at intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI for enhancing IoT applications with intelligent data processing and analytics capabilities.
By the end of this training, participants will be able to:
Understand the fundamentals of Edge AI and its application in IoT.
Set up and configure Edge AI environments for IoT devices.
Develop and deploy AI models on edge devices for IoT applications.
Implement real-time data processing and decision-making in IoT systems.
Integrate Edge AI with various IoT protocols and platforms.
Address ethical considerations and best practices in Edge AI for IoT.
This instructor-led, live training in Recife (online or onsite) is aimed at intermediate-level IT professionals and business managers who wish to understand the potential of IoT and edge computing for enabling efficiency, real-time processing, and innovation in various industries.
By the end of this training, participants will be able to:
Understand the principles of IoT and edge computing and their role in digital transformation.
Identify use cases for IoT and edge computing in manufacturing, logistics, and energy sectors.
Differentiate between edge and cloud computing architectures and deployment scenarios.
Implement edge computing solutions for predictive maintenance and real-time decision-making.
This instructor-led, live training in Recife (online or onsite) is aimed at product managers and developers who wish to use Edge Computing to decentralize data management for faster performance, leveraging smart devices located on the source network.
By the end of this training, participants will be able to:
Understand the basic concepts and advantages of Edge Computing.
Identify the use cases and examples where Edge Computing can be applied.
Design and build Edge Computing solutions for faster data processing and reduced operational costs.
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