6G and IoT Training Course

The primary goal of this training is to clarify what 5G networks are and how they impact smart technologies. We aim to demonstrate both the benefits and drawbacks of this technological synergy (5G/IoT) and explore the development trajectory of a network designed from the outset for the smart era.

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.

The Infrastructure and Network Design Ready for 6G program is a specialized training initiative designed to prepare current telecom and enterprise networks for the subsequent generation of wireless connectivity by leveraging advanced architectural and engineering methodologies. The curriculum addresses the evolution of transport and fronthaul networks, cloud-native and open RAN frameworks, edge and distributed computing capabilities, timing and synchronization requirements, spectrum and RF preparedness, automation and AI-driven operations, and actionable migration strategies tailored for both operators and enterprises.

This live, instructor-led training (available online or onsite) targets intermediate-level telecom engineers and network architects aiming to design, optimize, and evolve their existing 4G and 5G infrastructure to satisfy the performance, scalability, and reliability standards of 6G.

Upon finishing this course, participants will gain the ability to:

• Evaluate existing network infrastructure to identify gaps and assess readiness for 6G advancement.
• Architect transport and fronthaul/backhaul networks tailored for ultra-low latency and high throughput.
• Implement cloud-native principles, vRAN/O-RAN integration, and edge compute placement specific to 6G use cases.
• Schedule timing, synchronization, and RF enhancements necessary for mmWave/THz frequencies and dense network deployments.
• Establish testing, validation, and operational monitoring protocols to guarantee performance and reliability.
• Create a phased migration and investment roadmap that aligns with business objectives and risk management strategies.

Course Format

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

Customization Options

• For customized training requests regarding this course, please contact us to make arrangements.

This instructor-led, live training (available online or onsite) is designed for executive-level participants who want to grasp the global 6G landscape, evaluate its business potential, and prepare for early strategic investments. <\/p>

Upon completion of this course, participants will be equipped with the insights required to: <\/p>

• Recognize emerging market trends and global initiatives that are defining the 6G ecosystem. <\/li>
• Grasp regulatory frameworks and spectrum allocation schedules associated with IMT-2030. <\/li>
• Assess the changing vendor landscape and technology readiness levels. <\/li>
• Formulate a roadmap for early investment, research collaborations, and pilot programs. <\/li> <\/ul>

The course 'AI and Digital Twins in 6G Networks' provides an in-depth exploration of how artificial intelligence and digital twin technologies converge to model, simulate, and manage next-generation 6G infrastructure.

This instructor-led training, available online or on-site, is designed for advanced professionals seeking to apply digital twin methodologies and AI techniques to design, validate, and optimize 6G network behavior within realistic and reproducible environments.

Upon completing 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, transport, and edge computing 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 support 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 detailed architecture reviews.
• Practical labs involving simulators, twin models, and ML toolchains.
• Case study analyses and a hands-on mini-project integration exercise.

Customization Options

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

Technological advancements and the exponential growth of information are fundamentally reshaping business operations across numerous sectors, including the public sector. Government data generation and digital archiving volumes are surging, driven by the proliferation of mobile devices and applications, smart sensors and connected devices, cloud computing solutions, and citizen-facing digital portals. As digital information expands and becomes increasingly complex, the management, processing, storage, security, and disposition of that data become more intricate. Emerging 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 information as a strategic asset. Governments must now protect, leverage, and analyze both structured and unstructured information to better serve citizens and meet mission objectives. As government leaders strive to evolve into data-driven organizations, they are establishing the foundation to correlate dependencies across events, personnel, processes, and information.

High-impact government solutions will emerge from integrating the most disruptive technologies:

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

Big Data represents a transformative industry solution, empowering governments to make superior decisions by acting on patterns revealed through the analysis of vast volumes of data—both related and unrelated, structured and unstructured.

However, achieving this requires more than simply accumulating 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 from the White House Office of Science and Technology Policy in a post on the OSTP Blog.

The White House took a significant step toward supporting agencies in finding these technologies by establishing the National Big Data Research and Development Initiative in 2012. This initiative allocated over $200 million to capitalize on the explosion of Big Data and develop the necessary tools to analyze it.

The challenges posed by Big Data are nearly as daunting as the promise it offers. Efficiently storing data is one such challenge. With budgets always under pressure, agencies must minimize the cost per megabyte of storage while ensuring data remains easily accessible so users can retrieve it whenever and however they need it. Backing up these massive data volumes further intensifies the challenge.

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

Custom-developed Big Data tools are also allowing agencies to meet their data analysis needs. For instance, the Computational Data Analytics Group at Oak Ridge National Laboratory 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 routine tasks, such as sifting through resumes to match job candidates with hiring managers.

Insurtech, also known as Digital Insurance, represents the intersection of insurance and emerging technologies. Within this domain, "digital insurers" leverage technological innovations to refine their business models and operational frameworks, aiming to lower expenses, elevate customer satisfaction, and increase operational agility.

This instructor-led program provides participants with a comprehensive grasp of the technologies, methodologies, and strategic mindset required to drive digital transformation both within their own organizations and across the broader industry. The course is specifically designed for managers seeking a holistic understanding, aiming to cut through industry hype and jargon to take initial steps toward formulating an effective Insurtech strategy.

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

• Articulate the complexities of Insurtech and its various components with intelligence and structure
• Identify and demystify the function of each critical technology within the Insurtech ecosystem
• Develop a foundational strategy for implementing Insurtech solutions within their organization

Target Audience

• Insurance professionals
• Technology experts within the insurance sector
• Stakeholders in the insurance industry
• Consultants and business analysts

Course Format

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

This instructor-led live training in Romania (online or onsite) targets 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 different industries.

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

• Understand the foundational concepts of IoT and edge computing and their role in digital transformation.
• Identify use cases for IoT and edge computing in manufacturing, logistics, and energy.
• 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 Romania (online or onsite) is designed for 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.

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

• Grasp the fundamentals of Edge AI and its role in IoT.
• Set up and configure Edge AI environments tailored for IoT devices.
• Develop and deploy AI models on edge devices for IoT applications.
• Implement real-time data processing and decision-making within 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 Romania (online or onsite) targets product managers and developers aiming to utilize Edge Computing to decentralize data management for improved performance, capitalizing on smart devices at the network source.

Upon completion of this training, participants will be capable of:

• Comprehending the fundamental principles and benefits of Edge Computing.
• Recognizing specific use cases and examples suitable for Edge Computing implementation.
• Designing and constructing Edge Computing solutions to accelerate data processing and lower operational expenses.

Embedded systems are specialized computing devices 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 that connect, communicate, and share data via the internet.

This instructor-led live training, available online or on-site, targets beginner-level technical professionals aiming to grasp and apply embedded systems and IoT principles using C and microcontroller architectures.

Upon completing this course, participants will be capable of:

• Comprehending the architecture and components of embedded systems.
• Writing and compiling C code for direct embedded hardware interaction.
• Operating microcontroller peripherals, such as timers and ADCs.
• Understanding the role of embedded systems within IoT architectures.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical activities.
• Hands-on implementation in a live-lab setting.

Customization Options

• To arrange a customized training session for this course, please get in touch with us.

This instructor-led, live training in Romania (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 the advancements of 5G to deliver ultra-low latency, extreme throughput, pervasive intelligence, and integrated sensing capabilities for new application classes and services.

This instructor-led live training, available online or onsite, is designed for professionals ranging from beginner to intermediate levels who wish to grasp the technical foundations, regulatory landscape, and strategic business impacts of 6G to inform planning and decision-making.

After completing 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 Romania, 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.

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

• Identify the different components of NB-IoT and understand how they integrate to form an ecosystem.
• Understand and explain the security features embedded within 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 capabilities for your IoT solutions.

In this instructor-led live training, participants will learn how to integrate ThingsBoard into their IoT ecosystems.

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

• Install and configure ThingsBoard
• Grasp the fundamental features and architecture of ThingsBoard
• Develop IoT applications using ThingsBoard
• Integrate ThingsBoard with Kafka to route telemetry data from devices
• Integrate ThingsBoard with Apache Spark to aggregate data from 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 make arrangements.