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.

6G and the Intelligent Edge offers a forward-looking exploration into how 6G wireless technologies integrate with edge computing, IoT ecosystems, and AI-driven data processing to build intelligent, low-latency, and adaptive infrastructures.

This instructor-led, live training (available online or onsite) is designed for intermediate-level IT architects looking to understand and design next-generation distributed architectures by leveraging the synergy between 6G connectivity and intelligent edge systems.

After completing this course, participants will be able to:

• Grasp how 6G will transform edge computing and IoT architectures.
• Design distributed systems capable of ultra-low latency, high bandwidth, and autonomous operations.
• Integrate AI and data analytics at the edge to enable intelligent decision-making.
• Plan scalable, secure, and resilient infrastructures ready for 6G.
• Evaluate the business and operational models enabled by the convergence of 6G and edge technologies.

Format of the Course

• Interactive lectures and discussions.
• Case studies and applied architecture design exercises.
• Hands-on simulation using optional edge or container tools.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

The course on 6G-Ready Infrastructure and Network Design offers specialized training aimed at equipping existing telecom and enterprise networks for the upcoming generation of wireless connectivity. It utilizes advanced architectural and engineering methodologies to cover key areas such as the evolution of transport and fronthaul networks, cloud-native and Open RAN approaches, edge and distributed computing, timing and synchronization, RF and spectrum readiness, AI-native automation in operations, and practical migration strategies for both operators and enterprises.

Delivered as instructor-led, live training (available online or onsite), this program targets intermediate-level telecom engineers and network architects. Participants will learn how to design, optimize, and evolve their current 4G/5G infrastructure to satisfy the performance, scalability, and reliability demands of 6G.

After completing this course, participants will be capable of:

• Evaluating existing network infrastructure to identify gaps and assess readiness for 6G evolution.
• Designing transport and fronthaul/backhaul architectures optimized for ultra-low latency and high throughput.
• Implementing cloud-native principles, integrating vRAN/O-RAN, and planning edge compute placement for 6G applications.
• Planning the necessary timing, synchronization, and RF upgrades required for mmWave/THz frequencies and dense network deployments.
• Establishing testing, validation, and operational monitoring strategies to guarantee performance and reliability.
• Developing a phased migration and investment roadmap that aligns with business objectives and risk management protocols.

Course Format

• Technical lectures and in-depth architecture reviews.
• Case studies and design workshops.
• Practical labs utilizing simulation and verification tools.

Customization Options

• To request tailored training for this course, please reach out to us to make arrangements.

This instructor-led, live training session (available online or onsite) is designed for executive-level professionals seeking to comprehend the global 6G landscape, evaluate its business potential, and formulate early strategic investment plans.

Upon completing this course, participants will acquire the insights necessary to:

• Recognize emerging market trends and global initiatives that are defining the 6G ecosystem.
• Grasp the regulatory frameworks and spectrum allocation schedules associated with IMT-2030.
• Assess the dynamic vendor environment and current technology readiness stages.
• Construct a strategic roadmap for early investments, research collaborations, and pilot programs.

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.

The course 'AI and Digital Twins in 6G Networks' is an advanced, specialized program that examines the convergence of digital twin technology and AI-native optimization to model, simulate, and manage next-generation 6G infrastructures.

This instructor-led, live training (available online or onsite) is designed for advanced professionals seeking to apply digital twin methodologies and AI techniques to design, validate, and optimize 6G network behavior within realistic, reproducible environments.

Upon completing this training, participants will be able to:

• Describe the role and architecture of digital twins throughout the 6G network lifecycle.
• Create and configure digital twin models for RAN, transport, and edge compute components.
• Apply AI/ML methods for closed-loop optimization, anomaly detection, and predictive maintenance of network elements.
• Integrate real-time telemetry and simulation data to enable model-driven orchestration and intent-based control.
• Design validation and verification workflows using co-simulation, emulation, and digital twin testbeds.

Course Format

• Technical lectures and architecture deep-dives.
• Hands-on labs with simulators, twin models, and ML toolchains.
• Case study walkthroughs and a practical mini-project integration exercise.

Course Customization Options

• To request customized training for this course, please contact us to arrange.

Technological advancements and the exponential growth of data are reshaping operational practices across numerous sectors, including the public sector. Government data generation and digital archiving are accelerating, driven by the proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information becomes more voluminous and complex, the management, processing, storage, security, and retention of this data grow increasingly intricate. New tools for capture, search, discovery, and analysis are enabling organizations to derive valuable insights from unstructured data. The government sector is reaching a critical juncture, recognizing information as a strategic asset. Governments must now protect, leverage, and analyze both structured and unstructured data to fulfill mission requirements and serve the public more effectively. As government leaders work to evolve into data-driven organizations, they are establishing the foundation to correlate dependencies among events, personnel, processes, and information.

High-value government solutions will emerge from the integration of several disruptive technologies:

• Mobile devices and applications
• Cloud services
• Social business technologies and networking
• Big Data and analytics

Big Data represents an intelligent industry solution that empowers government entities to make better decisions by acting on patterns identified through the analysis of large volumes of data—both related and unrelated, structured and unstructured.

However, achieving these outcomes requires more than simply accumulating massive amounts of data. As Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy noted in a post on the OSTP Blog, "Making sense of these volumes of Big Data requires cutting-edge tools and technologies that can analyze and extract useful knowledge from vast and diverse streams of information."

The White House facilitated agency access to these technologies by establishing the National Big Data Research and Development Initiative in 2012. This initiative allocated over $200 million to maximize the potential of the Big Data explosion and the tools required to analyze it.

The challenges posed by Big Data are nearly as formidable as its potential is promising. Efficient data storage remains a primary challenge. With budgets often constrained, agencies must minimize storage costs per megabyte while ensuring data remains easily accessible for users to retrieve as needed. Backing up massive data volumes further complicates this task.

Effective data analysis presents another significant challenge. Many agencies utilize commercial tools to sift through vast data sets, identifying trends that enhance operational efficiency. (A recent MeriTalk study indicated that federal IT executives believe Big Data could help agencies save over $500 billion while meeting mission objectives).

Custom-developed Big Data tools are also enabling agencies to meet their analytical needs. For instance, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. This system has helped medical researchers identify links that can alert doctors to aortic aneurysms before they occur. It is also used for routine tasks, such as matching job candidates with hiring managers by reviewing resumes.

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.

Embedded systems are specialized computing devices designed to execute specific tasks within larger frameworks. IoT (Internet of Things) refers to a network of physical devices equipped with sensors and software, enabling them to communicate and share data via the internet.

This instructor-led live training, available either online or on-site, targets technical professionals at the beginner level who aim to grasp and apply embedded systems and IoT concepts using C programming and microcontroller architectures.

Upon completing this training, participants will be capable of:

• Comprehending the architecture and components of embedded systems.
• Writing and compiling C code to facilitate interaction with embedded hardware.
• Utilizing microcontroller peripherals, including timers and ADCs.
• Understanding the role of embedded systems within IoT architectures.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical applications.
• Hands-on implementation within a live laboratory environment.

Customization Options

• To request a customized training session for this course, please contact us to make arrangements.

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.

6G represents the next generation of wireless networking, building upon 5G advancements to deliver ultra-low latency, extremely high throughput, pervasive intelligence, and integrated sensing capabilities for a new class of applications and services.

This instructor-led live training (available online or onsite) is designed for beginner to intermediate professionals seeking to grasp the technical foundations, regulatory landscape, and strategic business impacts of 6G to inform planning and decision-making.

Upon completing this training, participants will be able to:

• Explain core 6G concepts and differentiate them from 5G.
• Identify key enabling technologies and their practical implications.
• Assess high-value use cases and industry verticals that 6G will support.
• Understand spectrum, regulatory, and policy considerations for 6G adoption.
• Draft a high-level 6G readiness roadmap for their organization.

Format of the Course

• Interactive lectures with conceptual walkthroughs.
• Case studies and sector-specific examples.
• Group workshop to develop an organizational 6G readiness outline.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

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.