6G and IoT Training Course

This training aims to clarify what a 5G network is and its influence on smart technologies. We will highlight both the advantages and limitations of the relationship between 5G and IoT, while exploring the development paths of a network designed from the outset for the smart world.

6G and the Intelligent Edge is a forward-thinking course that investigates the convergence of 6G wireless technologies with edge computing, IoT ecosystems, and AI-powered data processing to enable intelligent, low-latency, and adaptive infrastructures.

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

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

• Grasp how 6G will reshape edge computing and IoT architectures.
• Design distributed systems supporting ultra-low latency, high bandwidth, and autonomous operations.
• Integrate AI and data analytics at the edge to facilitate intelligent decision-making.
• Plan scalable, secure, and resilient infrastructures prepared for 6G.
• Evaluate 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.

This specialized training program focuses on equipping 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, RF and spectrum readiness, AI-native automation, and practical migration strategies for operators and enterprises.

This instructor-led, live training (available online or onsite) is designed for intermediate-level telecom engineers and network architects who aim 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:

• Evaluate 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.

Course Format

• 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 participants seeking to comprehend the global 6G landscape, evaluate its business potential, and strategize early investments.

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

• Recognize 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 landscape and technology readiness levels.
• Formulate a roadmap for early investment, research collaborations, and pilot projects.

The course on AI and Digital Twins in 6G Networks offers an advanced, specialized exploration into how digital twin technology and AI-native optimization intersect to model, simulate, and manage next-generation 6G infrastructures.

This instructor-led, live training, available online or onsite, 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 completing this training, participants will gain the ability to:

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

Course Format

• Technical lectures and in-depth architectural analyses.
• Hands-on labs utilizing simulators, twin models, and ML toolchains.
• Case study walkthroughs and a practical mini-project integration exercise.

Customization Options

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

Advancements in technology and the exponential growth of data are reshaping business operations across various sectors, including the public sector. Government data generation and digital archiving rates are accelerating due to the rapid proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information expands and becomes more complex, the management, processing, storage, security, and disposition of this data also grow more intricate. New capture, search, discovery, and analysis tools are enabling organizations to extract valuable insights from unstructured data. The government sector is reaching a tipping point, recognizing information as a strategic asset that must be protected, leveraged, and analyzed—both structured and unstructured—to better serve missions and meet requirements. As government leaders strive to evolve into data-driven organizations, they are laying the groundwork to correlate dependencies across events, people, processes, and information.

High-value government solutions will emerge from a combination of 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 enables government entities to make better decisions by acting on patterns revealed through the analysis of large volumes of data—both related and unrelated, structured and unstructured.

However, achieving these goals requires far more than simply accumulating massive quantities of data. As Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote 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."

In 2012, the White House took a significant step toward helping agencies identify these technologies by establishing the National Big Data Research and Development Initiative. This initiative allocated over $200 million to maximize the potential of the Big Data explosion and the tools needed to analyze it.

The challenges posed by Big Data are nearly as daunting as its promise is encouraging. Efficient data storage is one such challenge. With budgets always tight, agencies must minimize the per-megabyte cost of storage while keeping data easily accessible so users can retrieve it when and how they need it. Backing up massive quantities of data further heightens this challenge.

Effective data analysis presents another major hurdle. Many agencies use commercial tools to sift through vast amounts of data, identifying trends that help them operate more efficiently. A recent study by MeriTalk revealed 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 allowing agencies to address 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 find 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 session in Czech Republic (online or onsite) targets intermediate-level IT professionals and business managers who wish to understand how IoT and edge computing can drive efficiency, real-time processing, and innovation across various industries.

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

• Understand the fundamental principles of IoT and edge computing and their role in digital transformation.
• Identify relevant use cases for IoT and edge computing in manufacturing, logistics, and energy sectors.
• Differentiate between edge and cloud computing architectures and their deployment contexts.
• Implement edge computing solutions for predictive maintenance and real-time decision-making.

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

By the end 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.

Embedded systems are specialized computing platforms engineered to execute specific tasks within larger 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 exchange data via the internet.

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

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

• Comprehend the architecture and constituent elements of embedded systems.
• Write and compile C code to facilitate interaction with embedded hardware.
• Utilize microcontroller peripherals, including timers and Analog-to-Digital Converters (ADCs).
• Recognize the role embedded systems play within IoT architectures.

Course Format

• Engaging lectures paired with discussions.
• Ample opportunities for exercises and practical application.
• Hands-on implementation within a live laboratory environment.

Customization Options

• For those seeking a customized training experience, please reach out to us to make the necessary arrangements.

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

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

• Grasp the fundamental principles and advantages of Federated Learning in IoT and edge computing contexts.
• Deploy Federated Learning models on IoT devices to facilitate decentralized AI processing.
• Minimize latency and enhance real-time decision-making capabilities in edge computing environments.
• Overcome challenges associated with data privacy and network constraints in IoT systems.

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

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

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

• Explain core 6G concepts and how they differ from 5G.
• Identify key enabling technologies and their practical implications.
• Assess high-value use cases and industry verticals that 6G will enable.
• 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 Czech Republic (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.

In this instructor-led live training in Czech Republic, participants will learn how to maximize the performance of Nginx while setting it up, configuring it, monitoring it, and troubleshooting it to handle various forms of HTTP and TCP traffic. Covered topics include how to configure the most important parameters in Nginx, the operating system, and a virtual machine to gain maximum value from Nginx.

This instructor-led, live training in Czech Republic (online or onsite) targets intermediate-level IoT developers, embedded engineers, and AI practitioners aiming to implement TinyML for predictive maintenance, anomaly detection, and smart sensor applications.

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

• Grasp the core concepts of TinyML and its role in IoT.
• Establish a TinyML development environment for IoT initiatives.
• Create and deploy machine learning models on low-power microcontrollers.
• Apply TinyML for predictive maintenance and anomaly detection.
• Optimize TinyML models to maximize power efficiency and minimize memory usage.