6G and IoT Training Course

The objective of this training is to clarify the nature of 5G networks and their influence on smart technologies. The course aims to present both the advantages and disadvantages of the relationship between these technologies (5G and IoT), while highlighting the developmental directions of a network designed from the outset for the smart world.

6G and the Intelligent Edge is a forward-looking course that explores the integration of 6G wireless technologies with edge computing, IoT ecosystems, and AI-driven data processing to support intelligent, low-latency, and adaptive infrastructures.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT architects who wish to understand and design next-generation distributed architectures leveraging the synergy of 6G connectivity and intelligent edge systems.

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

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

Format of the Course

• Interactive lectures and discussions.
• Case studies and applied architecture design exercises.
• Hands-on simulation with 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, titled "Infrastructure and Network Design for 6G Readiness," is designed to prepare existing telecom and enterprise networks for the upcoming era of wireless connectivity by leveraging advanced architectural and engineering methodologies. The curriculum encompasses the evolution of transport and fronthaul networks, cloud-native and Open RAN strategies, edge and distributed computing, timing and synchronization protocols, spectrum and RF preparedness, automation and AI-driven operations, as well as practical migration strategies tailored for operators and enterprises.

Delivered as a live, instructor-led session (available online or on-site), this course targets intermediate-level telecom engineers and network architects seeking to design, optimize, and evolve their current 4G/5G infrastructure to satisfy the performance, scalability, and reliability demands of 6G.

Upon finishing this course, participants will be equipped to:

• Evaluate current network infrastructure to identify gaps and assess readiness for 6G evolution.
• Architect transport and fronthaul/backhaul systems optimized for ultra-low latency and high throughput.
• Implement cloud-native principles, vRAN/O-RAN integration, and edge compute placement specific to 6G use cases.
• Plan necessary timing, synchronization, and RF upgrades for dense deployments and mmWave/THz frequencies.
• Establish testing, validation, and operational monitoring strategies to guarantee performance and reliability.
• Develop a phased migration and investment roadmap aligned with business goals and risk management.

Course Format

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

Customization Options

• For requests for customized training on this course, please contact us to arrange it.

This instructor-led, live training (available online or onsite) targets executive-level professionals seeking to comprehend the global 6G landscape, evaluate its business potential, and strategize early investments.

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

• Recognize emerging market trends and global initiatives influencing the 6G ecosystem.
• Grasp the regulatory frameworks and spectrum allocation schedules associated with IMT-2030.
• Assess the shifting vendor landscape and varying levels of technological readiness.
• Construct a roadmap for early investments, 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 an instructor-led live training (available online or onsite), this program targets advanced professionals seeking to apply digital twin methodologies and AI techniques to design, validate, and optimize 6G network performance within realistic, reproducible environments.

Upon completion, participants will be able 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.
• Develop validation and verification workflows using co-simulation, emulation, and digital twin testbeds.

Course Format

• Technical lectures and in-depth architecture reviews.
• Practical labs involving simulators, twin models, and ML toolchains.
• Case study walkthroughs and a hands-on mini-project integration exercise.

Customization Options

• For customized training arrangements, please contact us.

Technological advancements and the exponential growth of information are reshaping business operations across various sectors, including government. The volume of data generated by government entities and the rate of digital archiving are increasing rapidly, driven by the proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information expands in complexity, managing, processing, storing, securing, and disposing of it becomes increasingly challenging. New tools for capturing, searching, discovering, and analyzing data are enabling organizations to derive valuable insights from unstructured data. The government sector is at a critical juncture, recognizing information as a strategic asset. Agencies must now protect, leverage, and analyze both structured and unstructured information to better serve the public and meet mission objectives. As government leaders work to transform their organizations into data-driven entities, they are establishing the framework to correlate dependencies across events, people, processes, and information.

High-impact government solutions are emerging 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 a transformative industry solution that enables governments to make better decisions by acting on patterns identified through the analysis of vast volumes of data—whether related or unrelated, structured or unstructured.

However, achieving these results requires more than just collecting large amounts 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," noted Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy in a post on the OSTP Blog.

The White House took significant steps to assist agencies in identifying these technologies by launching 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 necessary analytical tools.

The challenges presented by Big Data are as formidable as its promise is encouraging. Efficiently storing data is one such challenge. With budgets always under pressure, agencies must minimize storage costs per megabyte while ensuring data remains easily accessible so users can retrieve it whenever and however they need it. Backing up massive data volumes further complicates this task.

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

Custom-developed Big Data tools are also enabling 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 identify links that alert doctors to aortic aneurysms before they occur. It is also used for routine tasks, such as screening resumes to match job candidates with hiring managers.

This instructor-led, live training in Slovakia (online or onsite) is designed for intermediate 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.

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

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

This instructor-led, live training in Slovakia (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 solutions engineered to execute specific tasks within broader systems. The Internet of Things (IoT) 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 concepts related to embedded systems and IoT using C programming and microcontroller architectures.

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

• Grasp the architecture and key components 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).
• Comprehend the role of embedded systems within IoT architectures.

Course Format

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

Options for Course Customization

• For inquiries regarding customized training for this course, please reach out to us to make arrangements.

This instructor-led, live training in Slovakia (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 paradigm in wireless networking, leveraging advancements from 5G to facilitate ultra-low latency, extremely high throughput, pervasive intelligence, and integrated sensing capabilities. These improvements open the door to new classes of applications and services.

This instructor-led live training, available both online and onsite, is designed for beginner to intermediate-level professionals seeking to grasp the technical foundations, regulatory landscape, and strategic business implications of 6G for effective planning and decision-making.

Upon completing this training, participants will be able to:

• Explain core 6G concepts and highlight their differences from 5G.
• Identify key enabling technologies and understand 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 Slovakia (online or onsite) targets advanced-level IoT developers and smart home enthusiasts looking to automate IoT processes and build 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 conducted Slovakia, participants will learn how to maximize the performance of Nginx while setting up, configuring, monitoring, and troubleshooting it for handling various forms of HTTP and TCP traffic. The topics include configuring essential Nginx parameters, as well as optimizing the OS and virtual machine settings to gain maximum value from Nginx.

This instructor-led, live training in Slovakia (online or onsite) is aimed at 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:

• Understand the fundamentals of TinyML and its applications in IoT.
• Set up a TinyML development environment for IoT projects.
• Develop and deploy ML models on low-power microcontrollers.
• Implement predictive maintenance and anomaly detection using TinyML.
• Optimize TinyML models for efficient power and memory usage.