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.

This 21-hour training in Vietnam empowers IT architects to design next-generation distributed systems. We explore the integration of 6G, edge computing, and AI to create low-latency, scalable infrastructures. Develop practical skills to build secure, resilient, and intelligent edge architectures that align with future business requirements.

This instructor-led, live training in Vietnam guides intermediate telecom engineers in evolving 4G/5G infrastructure towards 6G. Covering cloud-native RAN, edge compute, and AI operations through hands-on labs and design workshops, the course facilitates the development of practical migration strategies.

This live, instructor-led program—delivered either online or on-site—is specifically tailored for executive leaders seeking to navigate the global 6G landscape, evaluate its commercial viability, and formulate early strategic investment plans.

Upon completion of this course, participants will possess the strategic insight required to:

• Recognize emerging market trends and global initiatives that are defining the 6G ecosystem.
• Navigate the regulatory environment and spectrum allocation schedules associated with IMT-2030.
• Assess the competitive vendor landscape alongside current levels of technology maturity.
• Formulate a strategic roadmap for initial capital deployment, research alliances, and pilot program implementation.

This advanced, instructor-led course in Vietnam delves into how digital twin technology and AI converge to model and operate next-generation 6G infrastructures. Learners will develop twin models, apply AI for closed-loop optimization, and integrate real-time telemetry to achieve intent-based network control.

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.

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.

Gain a foundational understanding of 6G’s technical and strategic elements in this accessible course. Delivered via Vietnam, it examines critical technologies, spectrum regulations, and high-impact use cases. Discover how 6G transcends 5G capabilities and draft a readiness roadmap to support informed strategic decisions within your organization.

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.