6G and IoT Training Course

This training aims to clarify the nature of 5G networks and their influence on smart technologies. We will explore the advantages and disadvantages of the relationship between 5G and IoT, while highlighting the developmental trajectory of a network designed from its inception for the smart world.

This forward-looking course examines the convergence of 6G wireless technologies with edge computing, IoT ecosystems, and AI-powered data processing to build intelligent, adaptive, and low-latency infrastructures.

Designed for intermediate-level IT architects, this instructor-led live training (available online or onsite) helps participants understand and design next-generation distributed architectures that leverage the synergy between 6G connectivity and intelligent edge systems.

Upon completion, participants will be able to:

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

Course Format

• Interactive lectures and guided discussions.
• Case studies and applied architecture design exercises.
• Hands-on simulation using optional edge or container tools.

Customization Options

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

The 6G-Ready Infrastructure and Network Design course is a specialized training program designed to help telecom and enterprise networks prepare for the next generation of wireless connectivity. Through advanced architectural and engineering practices, it covers transport and fronthaul evolution, cloud-native and open RAN approaches, edge and distributed compute, timing and synchronization, 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 want to design, optimize, and evolve their current 4G/5G infrastructure to meet the performance, scalability, and reliability requirements of 6G.

After 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.

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

This instructor-led live training (online or onsite) is designed for executives who wish to understand the global 6G landscape, assess its business potential, and plan early strategic investments.

By the end of this course, participants will gain the insights needed to:

• Identify emerging market trends and global initiatives shaping the 6G ecosystem.
• Understand regulatory and spectrum allocation timelines related to IMT-2030.
• Evaluate the evolving vendor landscape and technology readiness levels.
• Develop a roadmap for early investment, research partnerships, and pilot initiatives.

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

This instructor-led live training, available both online and onsite, targets advanced professionals seeking to leverage digital twin methodologies and AI techniques to design, validate, and optimize 6G network operations within realistic, reproducible environments.

Upon completing this training, participants will be equipped to:

• Explain 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 facilitate model-driven orchestration and intent-based control.
• Design validation and verification workflows leveraging co-simulation, emulation, and digital twin testbeds.

Course Format

• Technical lectures and deep dives into architecture.
• Practical labs involving simulators, twin models, and ML toolchains.
• Case study reviews and a practical mini-project integration exercise.

Customization Options

• For customized training arrangements, please contact us.

Technological advancements and the exponential growth of information are fundamentally reshaping business operations across various sectors, including government. The volume of government data generation and digital archiving is surging, driven by the rapid proliferation of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals. As digital information becomes more expansive and complex, the management, processing, storage, security, and disposition of this data also become increasingly complicated. New tools for capturing, searching, discovering, and analyzing information are helping organizations extract valuable insights from unstructured data. The government sector is reaching a critical juncture, recognizing information as a strategic asset. Governments must now protect, leverage, and analyze both structured and unstructured information to better serve the public and meet 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, people, 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 serves as an intelligent industry solution that enables governments to make better decisions by taking action based on patterns revealed through the analysis of large volumes of data—whether related or unrelated, structured or unstructured.

However, achieving these goals requires more than just 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," Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy noted 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 included over $200 million to capitalize on the explosion of Big Data 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 of these challenges. With budgets always tight, agencies must minimize the cost per megabyte of storage while keeping data easily accessible so users can retrieve it whenever and however they need it. The challenge is heightened by the need to back up massive quantities of data.

Effectively analyzing data is another major challenge. Many agencies employ commercial tools that allow them to sift through mountains of data, spotting 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. The 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.

Insurtech, also known as Digital Insurance, represents the intersection of insurance services and emerging technologies. Within this domain, 'digital insurers' leverage technological innovations to transform their business and operational models, aiming to lower costs, elevate customer experiences, and boost operational agility.

Through this instructor-led training, participants will acquire a comprehensive understanding of the technologies, methodologies, and mindsets required to drive digital transformation within their organizations and the broader industry. This program is specifically designed for managers who seek a holistic view, wish to cut through industry hype and jargon, and are ready to take initial steps toward establishing an effective Insurtech strategy.

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

• Discuss Insurtech and its various components with clarity and systematic insight
• Identify and demystify the role of each key technology driving Insurtech
• Develop a foundational strategy for implementing Insurtech within their respective organizations

Target Audience

• Insurance professionals
• Technology specialists within the insurance sector
• Key stakeholders in the insurance industry
• Consultants and business analysts

Course Format

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

This instructor-led live training in South Korea (online or onsite) is designed for intermediate-level IT professionals and business managers who wish to understand the potential of IoT and edge computing for enabling efficiency, real-time processing, and innovation in 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 South Korea (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 South Korea (online or onsite) targets product managers and developers who seek to utilize Edge Computing for decentralized data management, thereby enhancing performance through smart devices located at the network source.

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

• Grasp the fundamental concepts and benefits associated with Edge Computing.
• Recognize specific use cases and practical examples applicable to Edge Computing.
• Design and implement Edge Computing solutions that enable accelerated data processing and lower operational expenses.

Embedded systems are specialized computing platforms engineered to execute specific tasks within larger operational frameworks. The Internet of Things (IoT) refers to a vast network of physical devices integrated with sensors and software, enabling them to connect, communicate, and share 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 principles using C programming and microcontroller architectures.

Upon completing this training, participants will be capable of:

• Comprehending the architecture and constituent parts of embedded systems.
• Writing and compiling C code to facilitate hardware interaction.
• Operating microcontroller peripherals, such as timers and Analog-to-Digital Converters (ADCs).
• Understanding the role of embedded systems within IoT architectures.

Course Format

• Engaging lectures and group discussions.
• Extensive exercises and practical application.
• Practical implementation within a live laboratory environment.

Customization Options

• For customized training arrangements, please reach out to us.

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

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

• Grasp the core principles and advantages of Federated Learning within IoT and edge computing contexts.
• Deploy Federated Learning models on IoT devices to enable decentralized AI processing.
• Minimize latency and enhance real-time decision-making capabilities in edge computing environments.
• Address challenges related to data privacy and network constraints in IoT systems.

6G represents the next-generation wireless networking paradigm, building on 5G advances to enable ultra-low latency, extremely high throughput, pervasive intelligence, and integrated sensing capabilities for new classes of applications and services.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to understand the technical foundations, regulatory landscape, and strategic business impacts of 6G for 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 South Korea, 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 fit together 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 capabilities for your IoT solutions.

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

Upon completing this training, participants will be able to:

• Install and configure ThingsBoard
• Grasp the core concepts of ThingsBoard features and architecture
• 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 arrange customized training for this course, please contact us.