6G and IoT Training Course

This training aims to clarify what the 5G network is and its influence on smart technologies. It explores both the benefits and drawbacks of the 5G/IoT technological synergy, while highlighting the development trajectory of a network designed from the outset for the smart ecosystem.

"6G and the Intelligent Edge" is a forward-looking course that delves into 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:

• Grasp 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 Design Prepared for 6G program is a specialized training course designed to help existing telecom and enterprise networks get ready for the next generation of wireless connectivity through advanced architectural and engineering methods. The curriculum covers the evolution of transport and fronthaul networks, cloud-native and open RAN approaches, edge and distributed computing, timing and synchronization, spectrum and RF readiness, automation and AI-native operations, and practical migration strategies for operators and enterprises.

This instructor-led, live training (available online or onsite) is intended for 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.

Upon completing this course, participants will be able to:

• Evaluate current network infrastructure gaps and 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.

Format of the Course

• Technical lectures and architecture deep dives.
• Case studies and design workshops.
• Hands-on labs with simulation and verification tools.

Course Customization Options

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

This live, instructor-led training, offered online or onsite, targets executive-level participants seeking to understand the global 6G landscape, assess its commercial 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 course 'AI and Digital Twins in 6G Networks' is an advanced, specialized program that investigates how AI-native optimization and digital twin technology intersect to model, simulate, and manage next-generation 6G infrastructures.

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

Upon completing this training, participants will be able to:

• Describe the role and architecture of digital twins throughout the 6G network lifecycle.
• Create and configure digital twin models for RAN, transport, and edge compute 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 using co-simulation, emulation, and digital twin testbeds.

Course Format

• Technical lectures and in-depth architectural reviews.
• Practical labs utilizing simulators, twin models, and ML toolchains.
• Case study walkthroughs and a practical mini-project integration exercise.

Course Customization Options

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

Technological advancements and the exponential growth of information are fundamentally changing how businesses operate across various sectors, including government. The volume of government data generation and digital archiving is accelerating due to the widespread adoption of mobile devices and applications, smart sensors, cloud computing solutions, and public-facing digital portals. As digital information becomes more voluminous and complex, managing, processing, storing, securing, and disposing of this data presents greater challenges. Emerging tools for capturing, searching, discovering, and analyzing data are enabling organizations to extract valuable insights from unstructured information. The government sector is at a critical juncture, recognizing that information is a strategic asset. Governments must protect, leverage, and analyze both structured and unstructured data to better fulfill their missions and serve the public. As government leaders work to transform their organizations into data-driven entities, they are establishing the foundation to connect dependencies across events, personnel, processes, and information.

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

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

Big Data represents an intelligent industry solution that enables government agencies to make better decisions by acting on patterns identified through the analysis of vast amounts of data—both related and unrelated, structured and unstructured.

However, achieving this requires more than just accumulating large volumes 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 helping agencies identify these technologies by launching 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 necessary to analyze it.

The challenges posed by Big Data are nearly as formidable as its promise is promising. One such challenge is storing data efficiently. 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 when and how they need it. Backing up massive amounts of data further complicates this challenge.

Effective data analysis is another major hurdle. Many agencies utilize commercial tools to sift through vast data sets, identifying trends that enhance operational efficiency. (A recent MeriTalk study revealed that federal IT executives believe Big Data could help agencies save over $500 billion while also meeting mission objectives.)

Custom-developed Big Data tools are also enabling agencies to meet their analysis needs. For instance, the Computational Data Analytics Group at Oak Ridge National Laboratory 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 matching job candidates with hiring managers by sifting through resumes.

This instructor-led, live training in Mexico (online or onsite) is tailored for intermediate IT professionals and business managers who want to explore the potential of IoT and edge computing to enhance efficiency, enable real-time processing, and foster 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 Mexico (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.

Embedded systems are specialized computing systems engineered to execute specific tasks within larger frameworks. The Internet of Things (IoT) refers to a network of physical devices integrated with sensors and software, enabling them to communicate and exchange data via the internet.

This instructor-led live training, available online or onsite, is designed for technical professionals at the beginner level who aim to grasp and apply concepts of embedded systems and IoT using C programming and microcontroller architectures.

Upon completion of this training, participants will be capable of:

• Comprehending the architecture and components of embedded systems.
• Writing and compiling C code to interact with embedded hardware.
• Utilizing microcontroller peripherals, such as timers and ADCs.
• Understanding the role of embedded systems within IoT architectures.

Course Format

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

Customization Options for the Course

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

This instructor-led, live training in Mexico (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 in IoT and edge computing.
• 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 associated with data privacy and network limitations in IoT systems.

6G represents the next evolution in wireless networking, building upon the advancements of 5G to deliver ultra-low latency, massive throughput, pervasive intelligence, and integrated sensing. These capabilities open the door to new classes of applications and services.

This instructor-led live training, available online or on-site, is designed for beginner to intermediate professionals who want to grasp the technical foundations, regulatory environment, and strategic business implications of 6G to support planning and decision-making processes.

After completing this training, participants will be able to:

• Explain fundamental 6G concepts and how they differ from 5G.
• Identify key enabling technologies and their practical applications.
• Evaluate high-value use cases and industry sectors that 6G will support.
• Understand spectrum allocation, regulatory frameworks, and policy aspects relevant to 6G adoption.
• Develop a high-level 6G readiness roadmap tailored to 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.

Customization Options

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

This instructor-led, live training in Mexico (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 located in Mexico, participants will learn how to maximize the performance of Nginx by setting up, configuring, monitoring, and troubleshooting it for handling various forms of HTTP and TCP traffic. Topics covered include configuring the most important parameters in Nginx, the OS, and a virtual machine to gain maximum value out of Nginx.

This instructor-led, live training in Mexico (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.