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.

Insurtech (also known as Digital Insurance) represents the intersection of insurance and emerging technologies. Within the Insurtech landscape, "digital insurers" leverage technological innovations to transform their business and operational models, aiming to reduce costs, elevate the customer experience, and increase operational agility.

Through this instructor-led training, participants will develop a solid understanding of the technologies, methodologies, and mindset required to drive digital transformation within their organizations and across the industry. This training is specifically designed for managers who need to grasp the broader strategic context, cut through the hype and jargon, and take the initial steps toward establishing a robust Insurtech strategy.

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

• Discuss Insurtech and its various components with intelligence and systematic clarity
• Identify and clarify the role of each key technology within the Insurtech ecosystem.
• Develop a general strategy for implementing Insurtech solutions within their organization

Audience

• Insurance professionals
• Technology experts within the insurance industry
• Key insurance stakeholders
• Consultants and business analysts

Course Format

• A blend of lectures, discussions, exercises, and group case study activities

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.

This instructor-led, live training in Czech Republic (online or on-site) is designed for product managers and developers who wish to use Edge Computing to decentralize data management for improved performance, leveraging smart devices located on the source network.

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

• Understand the basic concepts and advantages of Edge Computing.
• Identify the use cases and examples where Edge Computing can be applied.
• Design and build Edge Computing solutions for faster data processing and reduced operational costs.

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.

In this instructor-led live training in Czech Republic, participants will explore the various aspects of NB-IoT (also known as LTE Cat NB1) while developing and deploying a sample NB-IoT-based application.

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

• Identify the different components of NB-IoT and how they integrate to form an ecosystem.
• Understand and explain the security features built into NB-IoT devices.
• Develop a simple application to track NB-IoT devices.

ThingsBoard is an open-source IoT platform that provides device management, data collection, processing, and visualization for your IoT ecosystem.

Through this instructor-led live training, participants will learn how to incorporate ThingsBoard into their IoT solutions.

Upon completing this training, participants will be capable of:

• Installing and configuring ThingsBoard
• Understanding the core concepts and architecture of ThingsBoard
• Developing IoT applications with ThingsBoard
• Integrating ThingsBoard with Kafka to route telemetry data from devices
• Integrating ThingsBoard with Apache Spark for data aggregation across multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Note

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