6G and IoT Training Course

The objective of this training is to clarify the nature of 5G networks and their impact on smart technologies. We aim to demonstrate both the advantages and disadvantages of the relationship between these technologies (5G and IoT), while highlighting the developmental trajectory 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.

The "Infrastructure and Network Architecture Ready for 6G" program is a specialized training course designed to help telecom providers and enterprise networks prepare for the next generation of wireless connectivity. It focuses on advanced architectural and engineering methods to evolve existing systems. Key topics include the evolution of transport and fronthaul networks, cloud-native and Open RAN strategies, edge and distributed computing, timing and synchronization, spectrum and RF readiness, AI-driven automation in operations, and practical migration plans 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 upgrade their current 4G/5G infrastructure to meet the performance, scalability, and reliability demands 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 that support 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 necessary 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 using 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 participants who aim 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.
• Understand regulatory frameworks and spectrum allocation timelines associated with IMT-2030.
• Assess the evolving vendor landscape and technology readiness levels.
• Formulate a roadmap for early investment, research partnerships, and pilot initiatives.

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

This instructor-led, live training (online or onsite) is aimed at advanced-level professionals who wish to apply digital twin methodologies and AI techniques to design, validate, and optimize 6G network behavior in realistic, reproducible environments.

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

• Explain the role and architecture of digital twins in the lifecycle of 6G networks.
• Build and configure digital twin models for RAN, transport, and edge compute components.
• Apply 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 reshaping business operations across numerous sectors, including the public sector. Government agencies are generating and archiving digital records at an accelerating pace, driven by the proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information becomes more voluminous and complex, the challenges associated with information management, processing, storage, security, and retention intensify. Emerging tools for capture, search, discovery, and analysis are enabling organizations to extract valuable insights from unstructured data. The government sector has reached a critical juncture where leaders recognize information as a strategic asset. To better serve citizens and meet mission requirements, governments must protect, leverage, and analyze both structured and unstructured information. As government leaders work to evolve into data-driven organizations, they are laying the groundwork to correlate dependencies across events, people, processes, and information.

High-value government solutions are being created through the integration of 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, enabling governments 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 more than just accumulating massive 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," wrote 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 advanced this effort by establishing the National Big Data Research and Development Initiative in 2012. This initiative allocated over $200 million to maximize the potential of Big Data and the tools required to analyze it.

The challenges posed by Big Data are nearly as formidable as its promise is encouraging. Efficiently storing data is one significant challenge. With budgets remaining tight, agencies must minimize the cost per megabyte of storage while ensuring data remains easily accessible so users can retrieve it efficiently. The need to back up massive amounts of data further exacerbates this challenge.

Effectively analyzing data presents another major hurdle. Many agencies utilize commercial tools to sift through large datasets, identifying trends that improve operational efficiency. (A recent MeriTalk study found 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 helping agencies meet their data analysis 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 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 integration of insurance services with emerging technologies. Within this domain, "digital insurers" leverage technological innovations to reshape their business and operational models, aiming to reduce costs, enhance customer experiences, and increase operational agility.

Through this instructor-led training, participants will develop a comprehensive understanding of the technologies, methodologies, and mindsets required to drive digital transformation within their organizations and across the broader industry. This course is designed for managers who seek a holistic overview, wish to cut through industry hype and jargon, and need guidance on taking initial steps toward formulating an Insurtech strategy.

Upon completing this training, participants will be equipped to:

• Discuss Insurtech and its various components with clarity and systematic insight
• Identify and demystify the role of each critical technology within the Insurtech ecosystem
• Develop a general strategy for implementing Insurtech solutions within their organization

Target Audience

• Insurance professionals
• Technologists working within the insurance sector
• Key stakeholders in the insurance industry
• Consultants and business analysts

Course Format

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

This instructor-led, live training in Taiwan (online or onsite) is designed for intermediate-level IT professionals and business managers who aim to understand the potential of IoT and edge computing for driving efficiency, real-time processing, and innovation across various industries.

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

• Grasp the foundational concepts of IoT and edge computing and their significance in digital transformation.
• Identify practical use cases for IoT and edge computing in manufacturing, logistics, and energy.
• 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 Taiwan (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:

• Grasp the fundamentals of Edge AI and its application in IoT.
• Establish and configure Edge AI environments for IoT devices.
• Create 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 Taiwan (online or onsite) targets product managers and developers who wish to decentralize data management for faster 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 dedicated tasks within broader operational frameworks. IoT (Internet of Things) refers to a network of physical devices equipped with sensors and software, enabling them to connect and exchange data via the internet.

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

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

• Comprehend the architecture and components of embedded systems.
• Write and compile C code for interacting with embedded hardware.
• Operate microcontroller peripherals such as timers and ADCs.
• Understand the role of embedded systems within IoT architectures.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Customization Options

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

This instructor-led, live training in Taiwan (online or onsite) targets intermediate-level professionals who wish to apply Federated Learning to optimize IoT and edge computing solutions.

Upon completing this training, participants will be able to:

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

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

This instructor-led live training (available online or onsite) is designed for beginner to intermediate-level professionals who wish to grasp the technical foundations, regulatory landscape, and strategic business impacts of 6G for effective 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 Taiwan, participants will learn about the various aspects of NB-IoT (also known as LTE Cat NB1) as they develop and deploy 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 to 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 solutions.

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

• Install and configure ThingsBoard
• Understand the fundamentals of ThingsBoard features and architecture
• Build IoT applications with ThingsBoard
• Integrate ThingsBoard with Kafka for telemetry device data routing
• Integrate ThingsBoard with Apache Spark for data aggregation from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

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