6G and IoT Training Course

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.

This 21-hour training in Italy guides IT architects in designing next-gen distributed systems. Explore 6G, edge computing, and AI integration for low-latency, scalable infrastructures. Gain practical skills for secure, resilient, and intelligent edge architectures to meet future business demands.

This instructor-led, live training in Italy equips intermediate telecom engineers to evolve 4G/5G infrastructure for 6G. It covers cloud-native RAN, edge compute, and AI operations through hands-on labs and design workshops, enabling practical migration strategies.

This instructor-led live training, delivered online or onsite, is curated for executive participants looking to grasp the global 6G landscape, assess its commercial viability, and plan proactive strategic investments.

By the conclusion of this course, participants will acquire the strategic clarity needed to:

• Spot emerging market trends and international efforts that are shaping the 6G ecosystem.
• Comprehend the regulatory frameworks and spectrum allocation timelines tied to IMT-2030.
• Assess the changing vendor landscape and the current levels of technological readiness.
• Formulate a roadmap for early investments, research collaborations, and pilot initiatives.

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.

This advanced, instructor-led course in Italy investigates how digital twin technology and AI converge to model and operate next-generation 6G infrastructures. Participants will develop twin models, implement AI for closed-loop optimization, and integrate real-time telemetry to achieve intent-based network control.

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.

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.

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.

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.

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.

Discover the technical and strategic underpinnings of 6G in this accessible, beginner-friendly course. Delivered in Italy, the curriculum explores essential technologies, spectrum policies, and high-impact use cases. Participants will learn to differentiate 6G from 5G and formulate a readiness roadmap to facilitate informed organizational decision-making.

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.