Online Internet of Things (IoT) Training in Italy

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

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

• Grasp the fundamentals of Edge AI and its specific applications in IoT contexts.
• Set up and configure Edge AI environments tailored for IoT devices.
• Create and deploy AI models on edge devices for IoT solutions.
• Implement real-time data processing and decision-making mechanisms within IoT systems.
• Integrate Edge AI capabilities with diverse IoT protocols and platforms.
• Address ethical considerations and adhere to best practices for Edge AI in IoT.

This instructor-led, live training in Italy (online or onsite) targets 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:

• Grasp the fundamentals of TinyML and its role in IoT.
• Configure a TinyML development environment tailored for IoT projects.
• Create and deploy ML models on low-power microcontrollers.
• Apply TinyML for predictive maintenance and anomaly detection.
• Optimize TinyML models to balance power efficiency and memory usage.

This instructor-led, live training in Italy (online or onsite) is designed for IT professionals and business managers at an intermediate level who wish to understand how IoT and edge computing can enhance efficiency, enable real-time processing, and foster innovation across various industries.

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

• Grasp the core principles of IoT and edge computing and their significance in digital transformation.
• Recognize specific use cases for IoT and edge computing within manufacturing, logistics, and energy industries.
• Distinguish between edge and cloud computing architectures and their respective deployment contexts.
• Deploy edge computing solutions to support predictive maintenance and real-time decision-making.

The primary goal of this training is to clarify the nature of 5G networks and their influence on smart technologies. We will explore both the benefits and drawbacks of the synergy between 5G and the Internet of Things (IoT), while outlining the developmental trajectory of a network ecosystem designed from the outset for the smart world.

Dive deeper into the innovative domain of edge computing with this advanced course. Explore complex architectures and tackle integration challenges, preparing to fully leverage the potential of edge computing across diverse business environments. Gain expertise in cutting-edge tools and methodologies to deploy, manage, and optimize edge computing solutions that address specific industry requirements.

Combine the transformative power of AI with the agility of edge computing in this comprehensive course. Learn to deploy AI models directly on edge devices, from understanding CNN architectures to mastering knowledge distillation and federated learning. This hands-on training will equip you with the skills to optimize AI performance for real-time processing and decision-making at the edge.

Establish a solid foundation in designing and managing resilient edge computing infrastructure. Gain insights into open hybrid cloud infrastructures, managing workloads across diverse cloud platforms, and ensuring flexibility and redundancy. This training provides essential knowledge for creating a scalable and secure infrastructure that supports the dynamic requirements of modern applications through edge computing.

In this instructor-led, live training held in Italy, participants will learn how to maximize Nginx's performance by setting up, configuring, monitoring, and troubleshooting it to handle various forms of HTTP and TCP traffic. The curriculum covers configuring essential Nginx parameters, alongside optimizing the operating system and virtual machine environments to derive the greatest benefit from Nginx.