6G and IoT Training Course

This training aims to clarify what the 5G network entails and its influence on smart technologies. It will illustrate both the advantages and disadvantages of the interplay between these technologies (5G/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 for 6G Readiness program is a specialized training course designed to help telecom and enterprise networks prepare for the next generation of wireless connectivity by applying advanced architectural and engineering techniques. Key topics include the evolution of transport and fronthaul networks, cloud-native and Open RAN methodologies, edge and distributed computing, timing and synchronization mechanisms, spectrum and RF preparedness, automation with AI-native operations, and practical migration strategies tailored for operators and businesses.

This live, instructor-led training is available online or onsite and 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 existing network infrastructure gaps and assess readiness for 6G evolution.
• Design transport and fronthaul/backhaul architectures capable of supporting ultra-low latency and high throughput.
• Implement cloud-native principles, integrate vRAN/O-RAN, and optimize edge compute placement for 6G use cases.
• Plan timing, synchronization, and RF upgrades necessary for mmWave/THz frequencies and dense network deployments.
• Establish testing, validation, and operational monitoring strategies to guarantee performance and reliability.
• 创建一份分阶段迁移和投资路线图，使其符合业务优先事项和风险管理要求。

Course Format

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

Customization Options

• For a customized version of this course, please contact us to arrange details.

This instructor-led, live training session (available online or onsite) targets executive-level professionals who aim to grasp the global 6G landscape, evaluate its business opportunities, and strategize early investments.

Upon completing this course, participants will acquire the knowledge required to:

• Recognize emerging market trends and international initiatives influencing the 6G ecosystem.
• Comprehend regulatory frameworks and spectrum allocation schedules concerning IMT-2030.
• Assess the changing vendor environment and technology readiness levels.
• Create a roadmap for early investment, research collaborations, and pilot projects.

AI and Digital Twins in 6G Networks is a specialized, advanced course that examines the convergence of digital twin technology with AI-native optimization to model, simulate, and manage next-generation 6G infrastructures.

This instructor-led live training (available online or onsite) targets advanced professionals aiming to utilize digital twin methodologies and AI techniques to design, validate, and optimize 6G network behavior within realistic, reproducible settings.

Upon completing this training, participants will gain the ability to:

• Describe the architecture and role of digital twins throughout the 6G network lifecycle.
• Construct and configure digital twin models for edge compute, transport, and RAN components.
• Utilize AI\/ML approaches for predictive maintenance, anomaly detection, and closed-loop optimization of network elements.
• Combine simulation data with real-time telemetry to facilitate intent-based control and model-driven orchestration.
• Develop verification and validation workflows employing digital twin testbeds, emulation, and co-simulation.

Course Format

• Architecture deep-dives and technical lectures.
• Practical labs involving simulators, twin models, and ML toolchains.
• Case study walkthroughs alongside 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 volume of government data generated and archived digitally is increasing rapidly, driven by the surge in mobile devices and applications, smart sensors and IoT devices, cloud computing solutions, and citizen-facing portals. As digital information becomes more expansive and complex, so do the challenges of managing, processing, storing, securing, and disposing of it. New tools for capturing, searching, discovering, and analyzing data are enabling organizations to extract valuable insights from unstructured information. The government sector is reaching a critical juncture, recognizing that information is a strategic asset. Governments must now protect, leverage, and analyze both structured and unstructured data to better serve the public and meet mission objectives. As government leaders work to evolve into data-driven organizations, they are building the foundation to correlate dependencies across events, personnel, processes, and information.

High-value government solutions will emerge from integrating 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 empowers governments to make better decisions by acting 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 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 took a significant step toward assisting agencies in finding these technologies by establishing the National Big Data Research and Development Initiative in 2012. 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 formidable as the opportunities it presents. Efficient data storage is a primary concern. With budgets remaining tight, agencies must minimize the cost per megabyte of storage while ensuring data remains easily accessible so users can retrieve it when and how they need it. Backing up vast quantities of data further intensifies this challenge.

Effective data analysis is another major hurdle. Many agencies utilize commercial tools that allow them to sift through mountains of data, identifying trends that enhance 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 enabling 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 identify links that can alert doctors to aortic aneurysms before they occur. It is also used for routine tasks, such as screening resumes to match job candidates with hiring managers.

This instructor-led live training in Vietnam (online or onsite) is designed for 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 various industries.

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

• Comprehend the foundational concepts of IoT and edge computing and their role in digital transformation.
• Identify specific use cases for IoT and edge computing in manufacturing, logistics, and energy.
• Differentiate between edge and cloud computing architectures and deployment scenarios.
• Apply edge computing solutions for predictive maintenance and real-time decision-making.

This instructor-led live training, located in Vietnam (offered online or onsite), is designed for intermediate-level developers, system architects, and industry professionals seeking to leverage Edge AI to augment IoT applications with sophisticated data processing and analytical capabilities.

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

• Comprehend the core principles of Edge AI and its integration into IoT systems.
• Prepare and configure Edge AI environments suitable for IoT device operation.
• Create and install AI models on edge devices to support IoT applications.
• Deploy real-time data processing mechanisms and decision-making algorithms in IoT systems.
• Connect Edge AI solutions with various IoT protocols and platform ecosystems.
• Address ethical concerns and adopt best practices for Edge AI deployment in IoT.

Embedded systems are specialized computing platforms designed to execute specific tasks within larger frameworks. The Internet of Things (IoT) refers to a network of physical devices equipped with sensors, software, and other technologies that enable them to connect and exchange data over the internet.

This instructor-led training session, available either online or onsite, targets beginner-level technical professionals seeking to grasp and implement embedded systems and IoT concepts using C programming 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 to facilitate interaction with embedded hardware.
• Utilizing microcontroller peripherals, including timers and Analog-to-Digital Converters (ADCs).
• Understanding the role of embedded systems within IoT architectures.

Course Format

• Engaging lectures and discussions.
• Extensive exercises and practical practice sessions.
• Hands-on implementation within a live laboratory environment.

Customization Options

• For tailored training needs, please contact us to arrange a customized program.

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

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

• Gain a solid understanding of the principles and advantages of Federated Learning in 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 within edge computing environments.
• Tackle challenges associated with data privacy and network limitations in IoT systems.

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

This instructor-led live training (available online or onsite) is designed for beginner to intermediate professionals seeking to grasp the technical foundations, regulatory landscape, and strategic business implications of 6G to inform planning and decision-making.

After completing this training, participants will be able to:

• Explain fundamental 6G concepts and their distinctions from 5G.
• Identify key enabling technologies and their practical applications.
• Evaluate high-value use cases and industry verticals enabled by 6G.
• Understand spectrum allocation, regulatory frameworks, and policy factors influencing 6G adoption.
• Develop a high-level 6G readiness roadmap for their organization.

Course Format

• Interactive lectures featuring conceptual walkthroughs.
• Case studies and industry-specific examples.
• Group workshop focused on creating an organizational 6G readiness outline.

Course Customization Options

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

This instructor-led, live training in Vietnam (online or onsite) is aimed at advanced-level IoT developers and smart home enthusiasts who wish to automate IoT processes and create innovative solutions using n8n.

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

• Set up and configure n8n for IoT workflow automation.
• Integrate IoT devices and platforms using n8n nodes and connectors.
• Implement custom workflows to automate IoT tasks and processes.
• Use IoT protocols like MQTT and REST APIs within n8n workflows.
• Monitor, troubleshoot, and optimize IoT automation workflows.

In this instructor-led live training in Vietnam, participants will learn how to maximize Nginx's performance by setting up, configuring, monitoring, and troubleshooting it for handling various forms of HTTP/TCP traffic. Topics covered include configuring key Nginx parameters, the operating system, and virtual machine settings to gain maximum value from Nginx.

This instructor-led, live training in Vietnam (online or onsite) is aimed at intermediate-level IoT developers, embedded engineers, and AI practitioners who wish to implement TinyML for predictive maintenance, anomaly detection, and smart sensor applications.

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

• Understand the fundamentals of TinyML and its applications in IoT.
• Set up a TinyML development environment for IoT projects.
• Develop and deploy ML models on low-power microcontrollers.
• Implement predictive maintenance and anomaly detection using TinyML.
• Optimize TinyML models for efficient power and memory usage.