Online Internet of Things (IoT) Training in Srbija

This instructor-led, live training in Srbija (online or onsite) is aimed at advanced-level IoT developers and smart home enthusiasts who wish to automate IoT processes and create innovative solutions using n8n.

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

• Set up and configure n8n for IoT workflow automation.
• Integrate IoT devices and platforms using n8n nodes and connectors.
• Implement custom workflows to automate IoT tasks and processes.
• Use IoT protocols like MQTT and REST APIs within n8n workflows.
• Monitor, troubleshoot, and optimize IoT automation workflows.

This instructor-led, live training in Srbija (online or onsite) is designed for intermediate-level professionals seeking to apply Federated Learning to optimize IoT and edge computing solutions.

Upon completion of this training, participants will be able to:

• Comprehend the principles and advantages of Federated Learning in IoT and edge computing.
• Deploy Federated Learning models on IoT devices for decentralized AI processing.
• Minimize latency and enhance real-time decision-making capabilities in edge computing environments.
• Overcome challenges related to data privacy and network limitations in IoT systems.

This instructor-led live training in Srbija (online or onsite) targets intermediate-level developers, system architects, and industry professionals eager to leverage Edge AI to boost IoT applications with intelligent data processing and analytics.

By the conclusion 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 Srbija (online or onsite) is designed for intermediate-level IoT developers, embedded engineers, and AI practitioners who wish to implement TinyML for predictive maintenance, anomaly detection, and smart sensor applications.

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

• Understand the fundamentals of TinyML and its applications in IoT.
• Set up a TinyML development environment for IoT projects.
• Develop and deploy ML models on low-power microcontrollers.
• Implement predictive maintenance and anomaly detection using TinyML.
• Optimize TinyML models for efficient power and memory usage.

Ovaj treninng pod vođstvom instruktora, koji se odvija uživo <lokalno> (online ili uživo na lokaciji), namenjen je IT profesionalcima srednjeg nivoa iskustva i poslovnim menadžerima koji žele da razumeju potencijal IoT-a i edge computinga za unapređenje efikasnosti, obradu podataka u realnom vremenu i inovacije u različitim industrijama.

Na kraju ovog treninga, učesnici će moći da:

• Razumeju principe IoT-a i edge computinga i njihovu ulogu u digitalnoj transformaciji.
• Identifikuju slučajeve primene IoT-a i edge computinga u sektorima proizvodnje, logistike i energije.
• Razlikuju arhitekturu i scenarije implementacije između edge i cloud computinga.
• Implementiraju rešenja za edge computing za prediktivno održavanje i donošenje odluka u realnom vremenu.

The aim of the training is to explain what the 5G network is and what impact it has on smart technologies. I want to show you both the advantages and disadvantages of these technological relationships (5G / IoT) and show you the directions of development of the network, which - from the very beginning - was dedicated to the smart world.

Delve deeper into the innovative realm of edge computing with this advanced course. Explore sophisticated architectures and tackle integration challenges, preparing to leverage the full potential of edge computing in a variety of business environments. Gain expertise in cutting-edge tools and methodologies to deploy, manage, and optimize edge computing solutions that meet specific industry needs.

Spojite transformativnu snagu AI-a i agilnost edge računarstva u ovom sveobuhvatnom kursu. Naučite da implementirate AI modele direktno na edge uređajima, od razumevanja CNN arhitektura dovladavanja destilacije znanja i federiranog učenja. Ovaj praktični trening će vam pružiti veštine potrebne za optimizaciju performansi AI-a za obradu u realnom vremenu i donošenje odluka na ivici mreže.

Establish a solid foundation in designing and managing resilient edge computing infrastructure. Gain insights into open hybrid cloud setups, workload management across various clouds, and strategies for ensuring flexibility and redundancy. This training equips learners with the essential knowledge needed to build scalable, secure infrastructure capable of supporting the dynamic demands of modern applications through edge computing.

In this instructor-led, live training conducted in Srbija, participants will learn to maximize Nginx's performance by configuring, monitoring, and troubleshooting it for various HTTP and TCP traffic scenarios. Key topics include configuring essential Nginx parameters, as well as optimizing the OS and virtual machine settings to achieve peak Nginx performance.