6G and IoT Training Course

This training aims to clarify the nature of 5G networks and their influence on smart technologies. We will explore both the advantages and disadvantages of the relationship between 5G and IoT, while highlighting the developmental trajectory of a network designed from its inception for the smart ecosystem.

This forward-looking course examines how 6G wireless technologies converge 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 seeking to understand and design next-generation distributed architectures that leverage the combined power of 6G connectivity and intelligent edge systems.

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

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

Format of the Course also allows for the evaluation of participants.

• 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 customized training for this course, please contact us to make arrangements.

This specialized training program, "Infrastructure and Network Design for 6G Readiness," is designed to prepare existing telecom and enterprise networks for the next generation of wireless connectivity through advanced architectural and engineering practices. The curriculum covers the evolution of transport and fronthaul networks, cloud-native and Open RAN approaches, edge and distributed computing, timing and synchronization, spectrum and RF readiness, automation and AI-native operations, and practical migration strategies for operators and enterprises.

This instructor-led live training (available online or onsite) is targeted at intermediate-level telecom engineers and network architects who wish to design, optimize, and evolve their current 4G/5G infrastructure to meet the performance, scalability, and reliability requirements of 6G.

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

• Assess current network infrastructure gaps and readiness for 6G evolution.
• Design transport and fronthaul/backhaul architectures suitable for ultra-low latency and high throughput.
• Apply cloud-native principles, vRAN/O-RAN integration, and edge compute placement for 6G use cases.
• Plan timing, synchronization, and RF upgrades required for mmWave/THz and dense deployments.
• Define testing, validation, and operational monitoring strategies to ensure performance and reliability.
• Develop a phased migration and investment roadmap aligned with business priorities and risk management.

Format of the Course also allows for the evaluation of participants.

• Technical lectures and architecture deep dives.
• Case studies and design workshops.
• Hands-on labs with simulation and verification tools.

Course Customization Options

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

This instructor-led, live training (available online or onsite) is designed for executive-level participants aiming to grasp the global 6G landscape, evaluate its business potential, and strategize early investments.

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

• Pinpoint emerging market trends and global initiatives influencing the 6G ecosystem.
• Comprehend regulatory frameworks and spectrum allocation schedules associated with IMT-2030.
• Assess the changing vendor environment and technology readiness levels.
• Create a roadmap for early investment, research collaborations, and pilot projects.

This advanced, specialized course examines how AI-native optimization and digital twin technology converge to model, simulate, and manage next-generation 6G infrastructures.

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

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

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

Course Format

• In-depth architectural analysis and technical lectures.
• Practical labs involving simulators, twin models, and ML toolchains.
• Case study walkthroughs and a practical mini-project integration exercise.

Course Customization Options

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

Advances in technology and the exponential growth of information are reshaping business operations across various sectors, including the government. The generation of government data and the pace of 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 expands and grows more complex, the management, processing, storage, security, and disposition of this data become increasingly challenging. New tools for capture, search, discovery, and analysis are enabling organizations to extract valuable insights from unstructured data. The government sector is at a critical juncture, recognizing that information is a strategic asset. Governments must now protect, leverage, and analyze both structured and unstructured information to better serve the public and fulfill mission requirements. As government leaders work to evolve their organizations into data-driven entities to successfully achieve their missions, they are establishing the foundation to correlate dependencies across events, personnel, processes, and information.

High-value government solutions will emerge from a convergence of the most disruptive technologies:

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

Big Data represents one of the intelligent industry solutions, enabling government entities to make better decisions by taking action based on patterns revealed through the analysis of large volumes of data—whether related or unrelated, structured or unstructured.

However, achieving these objectives requires far more than simply accumulating massive quantities of data. "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," Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote in a post on the OSTP Blog.

The White House took a significant step toward assisting agencies in finding 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 daunting as the promise it offers is encouraging. Efficient data storage is one such challenge. As budgets remain tight, agencies must minimize the per-megabyte cost of storage while keeping data easily accessible so users can retrieve it whenever and however they need it. Backing up massive amounts of data further complicates this challenge.

Effective data analysis is another major hurdle. Many agencies utilize commercial tools that allow them to sift through vast amounts of data, identifying trends that enhance operational efficiency. (A recent study by MeriTalk found that federal IT executives believe Big Data could help agencies save over $500 billion while also fulfilling mission objectives).

Custom-developed Big Data tools are also enabling agencies to meet the need for data analysis. For example, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. The system has helped medical researchers identify links that can alert doctors to aortic aneurysms before they occur. It is also used for more routine tasks, such as sifting through resumes to connect job candidates with hiring managers.

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

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

• Grasp the fundamental principles of IoT and edge computing and their significance in digital transformation.
• Recognize practical applications of IoT and edge computing in manufacturing, logistics, and energy sectors.
• Distinguish between edge and cloud computing architectures and their respective deployment scenarios.
• Deploy edge computing solutions to support predictive maintenance and real-time decision-making.

This instructor-led live training, conducted in France (online or onsite), is designed for intermediate developers, system architects, and industry professionals aiming to utilize Edge AI to enhance IoT applications with intelligent data processing and analytics.

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

• Comprehend 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.

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

This instructor-led live training, available online or onsite, is designed for technical professionals at the beginner level who aim to grasp and apply the principles of embedded systems and IoT using C programming and microcontroller architectures.

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

• Comprehend the architecture and core components of embedded systems.
• Draft and compile C code to facilitate interaction with embedded hardware.
• Operate microcontroller peripherals, including timers and Analog-to-Digital Converters (ADCs).
• Grasp the role of embedded systems within IoT architectures.

Course Format

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

Customization Options

• For a tailored training experience, please contact us to arrange your specific requirements.

This instructor-led, live training in France (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, massive throughput, pervasive intelligence, and integrated sensing for new application categories 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 environment, and strategic business implications of 6G to inform planning and decision-making.

Upon completing this training, participants will be able to:

• Explain fundamental 6G concepts and their distinctions from 5G.
• Identify key enabling technologies and their practical implications.
• Evaluate high-value use cases and industry verticals enabled by 6G.
• Understand spectrum allocation, regulatory frameworks, and policy factors impacting 6G adoption.
• Draft a high-level 6G readiness roadmap for their organization.

Course Format

• Interactive lectures featuring conceptual walkthroughs.
• Case studies and industry-specific examples.
• Group workshop to create an organizational 6G readiness outline.

Customization Options

• To request a customized training version of this course, please contact us to arrange your schedule.

This instructor-led live training in France (online or onsite) is designed for advanced IoT developers and smart home enthusiasts who wish to automate IoT processes and create innovative solutions using n8n.

Upon completing 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.
• Utilize IoT protocols such as MQTT and REST APIs within n8n workflows.
• Monitor, troubleshoot, and optimize IoT automation workflows.

In this instructor-led live training conducted in France, participants will learn how to maximize the performance of Nginx by setting it up, configuring, monitoring, and troubleshooting it to handle various forms of HTTP and TCP traffic. Covered topics include configuring critical parameters in Nginx, the OS, and a virtual machine to gain maximum value from Nginx.

This instructor-led, live training in France (online or onsite) is designed for intermediate-level IoT developers, embedded engineers, and AI practitioners who want to apply TinyML for predictive maintenance, anomaly detection, and smart sensor solutions.

Upon completing this training, participants will be able to:

• Grasp the core principles of TinyML and its role in IoT ecosystems.
• Configure a TinyML development environment tailored for IoT projects.
• Create and deploy machine learning models on low-power microcontrollers.
• Apply TinyML techniques for predictive maintenance and anomaly detection.
• Refine TinyML models to maximize power efficiency and minimize memory consumption.