6G and IoT Training Course

The primary goal of this training is to clarify what the 5G network entails and its influence on smart technologies. I aim to illustrate both the benefits and drawbacks of this technological synergy (5G / IoT) and outline the development trajectory of the network, which has been oriented toward the smart world from its inception.

The '6G and the Intelligent Edge' course offers a forward-looking perspective on integrating 6G wireless technologies with edge computing, IoT ecosystems, and AI-driven data processing to enable intelligent, adaptive, and low-latency infrastructures.

This instructor-led training, available online or onsite, targets intermediate-level IT architects seeking to grasp and design next-generation distributed architectures that leverage the synergy between 6G connectivity and intelligent edge systems.

Upon completing this course, participants will be able to:

• Comprehend 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 to facilitate intelligent decision-making.
• Plan scalable, secure, and resilient 6G-ready edge infrastructures.
• Evaluate business and operational models enabled by the convergence of 6G and edge technologies.

Course Format

• 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.

The "6G-Ready Infrastructure and Network Design" program is a specialized training initiative designed to equip telecom and enterprise networks for the next generation of wireless connectivity through advanced architectural and engineering methodologies. The curriculum explores the evolution of transport and fronthaul networks, cloud-native and Open RAN methodologies, edge and distributed computing, timing and synchronization mechanisms, spectrum and RF readiness, automation and AI-native operations, as well as practical migration strategies for operators and enterprises.

This instructor-led, live training (available online or onsite) targets 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 completing this course, participants will be able to:

• Evaluate current network infrastructure gaps and assess 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

• 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 professionals seeking to grasp the global 6G landscape, evaluate its business opportunities, and formulate early strategic investment plans.

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

• Recognize emerging market trends and global initiatives influencing the 6G ecosystem.
• Comprehend regulatory frameworks and spectrum allocation schedules tied to IMT-2030.
• Analyze the shifting vendor landscape and assess technology readiness levels.
• Establish a roadmap for early investment, research collaborations, and pilot projects.

The course "AI and Digital Twins in 6G Networks" is an advanced, specialized program that examines how digital twin technology and AI-native optimization converge to model, simulate, and operate next-generation 6G infrastructures.

This instructor-led, live training (available online or onsite) is designed for advanced-level professionals who aim 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 role and architecture of digital twins in the lifecycle of 6G networks.
• Construct and configure digital twin models for RAN, transport, and edge compute components.
• Implement 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.

Format of the Course

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

Technological advancements and the exponential growth of information are fundamentally reshaping business operations across various sectors, including government. The generation of government data and digital archiving rates are surging, driven by the rapid proliferation of mobile devices and applications, smart sensors and IoT devices, cloud computing solutions, and citizen-facing portals. As digital information expands in volume and complexity, the challenges associated with information management, processing, storage, security, and disposition become increasingly intricate. Emerging tools for capture, search, discovery, and analysis are enabling organizations to extract valuable insights from unstructured data. The government sector is reaching a critical tipping point, recognizing that information is a strategic asset. Consequently, governments must protect, leverage, and analyze both structured and unstructured information to better fulfill mission requirements. As government leaders strive to evolve into data-driven organizations to successfully accomplish their missions, they are laying the groundwork to correlate dependencies across events, personnel, processes, and information.

High-value government solutions will emerge from a combination 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 that enable governments to make better decisions by taking action based 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. "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 a significant step toward helping agencies identify these technologies by establishing the National Big Data Research and Development Initiative in 2012. This initiative allocated more than $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 its promise is encouraging. One significant challenge is efficient data storage. 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 exacerbates this challenge.

Effectively analyzing data presents another major hurdle. Many agencies utilize commercial tools that allow them to sift through mountains of data, identifying trends that help them operate more efficiently. (A recent study by MeriTalk found that federal IT executives believe Big Data could help agencies save more than $500 billion while also fulfilling mission objectives.)

Custom-developed Big Data tools are also enabling agencies to address their data analysis needs. For example, 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 more routine tasks, such as sifting through resumes to connect job candidates with hiring managers.

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

Upon completing this training, participants will be able to:

• Comprehend the core principles of IoT and edge computing and their significance in digital transformation.
• Recognize specific use cases for IoT and edge computing within the manufacturing, logistics, and energy industries.
• Distinguish between edge and cloud computing architectures, as well as their respective deployment scenarios.
• Deploy edge computing solutions to support predictive maintenance and real-time decision-making processes.

This instructor-led, live training in Bulgaria (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 broader technological frameworks. The Internet of Things (IoT) refers to a vast network of physical devices equipped with sensors and software, enabling them to communicate and exchange data via the internet.

This instructor-led training session, available both online and onsite, is tailored for entry-level technical professionals eager to grasp and implement embedded systems and IoT principles using C programming and microcontroller architectures.

Upon completing this training, participants will be capable of:

• Gaining a thorough understanding of embedded system architecture and its constituent parts.
• Writing and compiling C code to facilitate interaction with embedded hardware.
• Operating microcontroller peripherals, including timers and ADCs.
• Comprehending the role embedded systems play within IoT architectures.

Course Format

• Engaging lectures and group discussions.
• Extensive practical exercises and hands-on practice.
• Live-lab implementation exercises.

Customization Options

• For tailored training on this subject, please reach out to us to make arrangements.

This instructor-led, live training in Bulgaria (online or onsite) is tailored for 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, leveraging advancements from 5G to deliver ultra-low latency, massive throughput, pervasive intelligence, and integrated sensing for a new era of applications and services.

This instructor-led 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.

After completing this training, participants will be able to:

• Articulate core 6G concepts and distinguish them from 5G.
• Recognize key enabling technologies and their practical applications.
• Evaluate high-value use cases and industry sectors that 6G will unlock.
• Understand spectrum allocation, regulatory frameworks, and policy factors influencing 6G adoption.
• Create a high-level roadmap for 6G readiness within their organization.

Course Format

• Interactive lectures with conceptual walkthroughs.
• Case studies and industry-specific examples.
• Group workshop focused on developing an organizational 6G readiness outline.

Customization Options

• For customized training requests, please contact us to arrange.

This hands-on course offers a thorough introduction to the Internet of Things (IoT), spanning from device-level programming to cloud-based data processing and visualization. Participants will examine the entire IoT architecture—including sensors, communication protocols, microcontrollers, and cloud integration—through guided exercises utilizing development boards such as ESP32 and Raspberry Pi. Upon completing the course, learners will be equipped to construct a full IoT pipeline: capturing sensor data, transmitting it via MQTT/HTTP, processing it on cloud platforms like Azure IoT Hub, AWS IoT Core, or Google Cloud IoT, and visualizing it using tools such as Grafana or Power BI. The curriculum also addresses security best practices and simulated cyber threats to guarantee secure and robust deployments.

This instructor-led, live training in Bulgaria (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 completion of this training, participants will be able to:

• Install and configure n8n for IoT workflow automation.
• Connect IoT devices and platforms utilizing n8n nodes and connectors.
• Develop custom workflows to automate IoT tasks and operational 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 Bulgaria, participants will learn how to maximize Nginx's performance by setting up, configuring, monitoring, and troubleshooting it to manage various forms of HTTP and TCP traffic. The curriculum covers the configuration of critical Nginx parameters, along with OS and virtual machine adjustments, to ensure optimal utilization of Nginx.

This instructor-led, live training in Bulgaria (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.