6G and IoT Training Course

6G and the Intelligent Edge is an advanced course that delves into the integration of 6G wireless technologies with edge computing, IoT ecosystems, and AI-driven data processing. This course focuses on creating intelligent, low-latency, and adaptive infrastructures.

This instructor-led, live training (available both online and onsite) is designed for intermediate-level IT architects who want to gain a deep understanding of how to 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:

• Understand how 6G technology will revolutionize edge computing and IoT architectures.
• Design distributed systems that support 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.
• Evaluate new business and operational models made possible by the convergence of 6G and edge computing.

Format of the Course

• Interactive lectures and discussions.
• Case studies and practical architecture design exercises.
• Hands-on simulations 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 aimed at preparing existing telecom and enterprise networks for the next generation of wireless connectivity. This involves advanced architectural and engineering practices covering transport and fronthaul evolution, cloud-native and open RAN approaches, edge and distributed computing, timing and synchronization, spectrum and RF readiness, automation, AI-native operations, and practical migration strategies for operators and enterprises.

This instructor-led, live training (available online or on-site) is designed for intermediate-level telecom engineers and network architects who are looking 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 existing network infrastructure gaps and readiness for 6G evolution.
• Design transport and fronthaul/backhaul architectures that support ultra-low latency and high throughput.
• Implement 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.
• Establish testing, validation, and operational monitoring strategies to ensure performance and reliability.
• Develop a phased migration and investment roadmap that aligns with business priorities and risk management.

Format of the Course

• Technical lectures and in-depth architecture discussions.
• Case studies and design workshops.
• Hands-on labs using simulation and verification tools.

Course Customization Options

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

This instructor-led, live training (online or onsite) is aimed at executive-level participants 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.

AI and Digital Twins in 6G Networks is an advanced, specialized course that delves into the integration of digital twin technology and AI-native optimization 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 the behavior of 6G networks in realistic, reproducible environments.

Upon completing this training, participants will be able to:

• Explain the role and architecture of digital twins throughout the lifecycle of 6G networks.
• Build and configure digital twin models for RAN, transport, and edge computing 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 in-depth architecture discussions.
• 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 practices across various sectors, including government. The surge in mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals is driving a significant increase in data generation and digital archiving within government entities. As the volume and complexity of digital information expand, the challenges related to managing, processing, storing, securing, and disposing of this data become more intricate. However, new tools for capturing, searching, discovering, and analyzing unstructured data are enabling organizations to derive valuable insights. The government sector is at a critical juncture, recognizing that information is a strategic asset. To better serve the public and meet mission requirements, government agencies need to protect, leverage, and analyze both structured and unstructured information. As leaders strive to transform their organizations into data-driven entities, they are establishing frameworks to identify and correlate dependencies across events, people, processes, and information.

High-impact government solutions will emerge from the integration of the most transformative technologies:

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

Big Data is a key intelligent industry solution that enables government agencies to make informed decisions by analyzing large volumes of data—both structured and unstructured. By identifying patterns within these vast datasets, governments can take more effective actions.

However, achieving these outcomes requires more than just collecting massive amounts of data. "Interpreting such vast quantities of Big Data necessitates cutting-edge tools and technologies capable of analyzing and extracting meaningful insights from diverse streams of information," Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote in a blog post.

In 2012, the White House took a significant step toward helping agencies find these necessary tools by launching the National Big Data Research and Development Initiative. This initiative allocated over $200 million to capitalize on the surge in Big Data and develop the required analytical tools.

The challenges posed by Big Data are as formidable as its potential is promising. Efficient data storage is a major challenge, especially given budget constraints. Agencies must reduce the cost per megabyte of storage while ensuring easy access for users when and how they need it. Backing up large volumes of data further complicates this task.

Effective data analysis presents another significant challenge. Many agencies use commercial tools to sift through vast datasets, identifying trends that can enhance operational efficiency. A recent study by MeriTalk found that federal IT executives believe Big Data could help agencies save more than $500 billion while also achieving their mission objectives.

Custom-developed Big Data tools are also aiding agencies in analyzing their data. 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 a critical link that can alert doctors to potential aortic aneurysms before they occur. It is also used for more routine tasks, such as filtering through resumes to match job candidates with hiring managers.

Insurtech, or Digital Insurance, represents the integration of insurance with cutting-edge technologies. In this domain, "digital insurers" leverage technological innovations to streamline their business and operational models, aiming to cut costs, enhance customer experiences, and boost operational agility.

This instructor-led training equips participants with a comprehensive understanding of the technologies, methodologies, and mindset required for digital transformation within their organizations and across the industry. The training is designed for managers who need an overarching view to separate fact from hype, demystify jargon, and take initial steps in formulating an Insurtech strategy.

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

• Engage in intelligent and systematic discussions about Insurtech and its various components.
• Clearly identify and understand the role of each key technology within Insurtech.
• Develop a general strategy for implementing Insurtech within their organization.

Audience

• Insurance companies
• Technologists in the insurance sector
• Insurance stakeholders
• Consultants and business analysts

Format of the course

• A combination of lectures, discussions, exercises, and group activities centered around case studies.

This instructor-led, live training in Taiwan (online or onsite) is aimed at 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 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:

• 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 Taiwan (online or onsite) is aimed at product managers and developers who wish to use Edge Computing 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.

This instructor-led, live training in Taiwan (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 wireless networking paradigm, building on the advancements of 5G to deliver ultra-low latency, extremely high throughput, pervasive intelligence, and integrated sensing capabilities for a new generation of applications and services.

This instructor-led, live training (available both online and onsite) is designed for professionals at beginner to intermediate levels who wish to gain a deep understanding of the technical foundations, regulatory landscape, and strategic business impacts of 6G. The training aims to equip participants with the knowledge needed for effective planning and decision-making.

Upon completing this training, participants will be able to:

• Explain the core concepts of 6G and how they differ from those of 5G.
• Identify key enabling technologies and their practical implications in real-world scenarios.
• Evaluate high-value use cases and industry verticals that will be transformed by 6G.
• Understand the spectrum, regulatory, and policy considerations essential for 6G adoption.
• Develop a high-level roadmap to prepare their organization for 6G readiness.

Format of the Course

• Interactive lectures featuring conceptual walkthroughs.
• Case studies and examples specific to various sectors.
• A group workshop to create an organizational 6G readiness outline.

Course Customization Options

• For a customized training session tailored to your specific needs, please contact us to arrange.

Unlike other technologies, the Internet of Things (IoT) is far more intricate, encompassing nearly every branch of core engineering—mechanical, electronics, firmware, middleware, cloud, analytics, and mobile. Each layer of IoT involves various aspects of economics, standards, regulations, and evolving state-of-the-art advancements. This course is a comprehensive introduction to the critical aspects of IoT Engineering, offering a unique and detailed exploration of this multifaceted technology.

Summary

An advanced training program covering the latest developments in Internet of Things (IoT)

This course spans multiple technological domains to provide an understanding of IoT systems and their components, as well as how they can benefit businesses and organizations.

Live demonstrations of model IoT applications will showcase practical deployments across various industry sectors, such as Industrial IoT, Smart Cities, Retail, Travel & Transportation, and use cases involving connected devices and things.

Target Audience

This course is designed for managers responsible for business and operational processes within their organizations who want to learn how to leverage IoT to enhance the efficiency of their systems and processes.

Entrepreneurs and investors interested in building new ventures will gain a deeper understanding of the IoT technology landscape, enabling them to effectively leverage it in their projects.

The market value estimates for Internet of Things (IoT) are substantial, as by definition, IoT is an integrated and pervasive layer of devices, sensors, and computing power that spans consumer, business-to-business, and government industries. By 2018, the number of IoT connections is projected to reach 9 billion, roughly equivalent to the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

In the consumer market, numerous products and services have already integrated with the IoT, including kitchen and home appliances, parking systems, RFID, lighting and heating solutions, and various applications in the Industrial Internet.

While the underlying technologies of IoT are not new—machine-to-machine (M2M) communication has existed since the inception of the internet—the recent emergence of inexpensive wireless technologies and the widespread adoption of smartphones and tablets have driven the explosive growth of mobile devices, leading to the current demand for IoT solutions.

The vast opportunities in the IoT business have attracted a large number of small and medium-sized entrepreneurs. The availability of open-source electronics and IoT platforms has made it increasingly affordable to develop and manage IoT systems on a significant scale. Existing electronic product manufacturers are under pressure to integrate their devices with the internet or mobile apps.

This training program aims to provide a technology and business review of this emerging industry, helping IoT enthusiasts and entrepreneurs grasp the basics of IoT technology and its business potential.

Course Objective

The primary goal of the course is to introduce participants to the latest technological options, platforms, and case studies of IoT implementation in areas such as home and city automation (smart homes and cities), Industrial Internet, healthcare, government, mobile cellular networks, and other sectors.

It will cover a basic introduction to all elements of IoT, including mechanical components, electronics/sensor platforms, wireless and wireline protocols, integration of mobile devices with electronics, enterprise integration, data analytics, and the total control plane.

The course will also delve into M2M wireless protocols for IoT, such as WiFi, Zigbee/Zwave, Bluetooth, and ANT+, discussing when and where to use each one.

It will explore mobile/desktop/web applications for registration, data acquisition, and control, along with available M2M data acquisition platforms like Xively, Omega, and NovoTech.

The training will address security issues and solutions specific to IoT.

Participants will learn about open-source and commercial electronics platforms for IoT, such as Raspberry Pi, Arduino, and ArmMbedLPC.

The course will also cover open-source and commercial enterprise cloud platforms for AWS-IoT apps, Azure-IOT, Watson-IOT cloud, and other minor IoT clouds.

Finally, it will include case studies of common IoT devices like home automation systems, smoke alarms, vehicles, military applications, and home health solutions.

Machine-to-Machine (M2M) involves the automated exchange of information and commands between interconnected mechanical or electronic devices.

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 for your IoT solutions.

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

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

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

Audience

• Software engineers
• Hardware engineers
• Developers

Format of the course

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

Note

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