6G and IoT Training Course

This training aims to clarify what the 5G network is and its impact on smart technologies. We will examine both the advantages and disadvantages of the relationship between these technologies (5G / IoT) and explore the developmental directions of a network that has been dedicated to the smart world from its inception.

6G and the Intelligent Edge is an innovative course that investigates the convergence of 6G wireless technologies, edge computing, IoT ecosystems, and AI-powered data processing to build intelligent, adaptive, and low-latency infrastructures.

This instructor-led live training (available online or onsite) targets intermediate-level IT architects looking to master and design next-generation distributed architectures that leverage the combined strengths of 6G connectivity and intelligent edge systems.

After completing this course, participants will be able to:

• Grasp how 6G will revolutionize edge computing and IoT architectures.
• Develop distributed systems for autonomous operations, high bandwidth, and ultra-low latency.
• Implement AI and data analytics at the edge to enable intelligent decision-making.
• Architect scalable, secure, and resilient edge infrastructures prepared for 6G.
• Assess the business and operational models facilitated by the convergence of 6G and edge computing.

Course Format

• Interactive lectures and discussions.
• Case studies and applied architecture design exercises.
• Hands-on simulation using optional edge or container tools.

Course Customization Options

• For customized training arrangements, please contact us.

The course on Infrastructure and Network Design for 6G Readiness is a specialized training initiative designed to equip existing telecom and enterprise networks with the advanced architectural and engineering practices necessary for the next generation of wireless connectivity. The curriculum encompasses the evolution of transport and fronthaul networks, cloud-native and open RAN methodologies, edge and distributed computing, precise timing and synchronization, spectrum and RF preparedness, automation alongside AI-native operations, and practical migration strategies tailored for operators and enterprise clients.

This live, instructor-led training, available in online or onsite formats, targets intermediate-level telecom engineers and network architects. Their goal is to design, optimize, and evolve their current 4G and 5G infrastructure to satisfy the performance, scalability, and reliability demands of 6G.

Upon completing this course, participants will be able to:

• Evaluate current network infrastructure gaps and assess readiness for 6G evolution.
• Architect transport and fronthaul/backhaul solutions suitable for ultra-low latency and high throughput.
• Implement cloud-native principles, vRAN/O-RAN integration, and strategic edge compute placement for 6G applications.
• Plan the necessary timing, synchronization, and RF upgrades required for mmWave/THz frequencies and dense network deployments.
• Establish testing, validation, and operational monitoring strategies to guarantee performance and reliability.
• Create a phased migration and investment roadmap aligned with business priorities and risk management.

Course Format

• Technical lectures and in-depth architectural reviews.
• Case studies and design workshops.
• Practical labs utilizing simulation and verification tools.

Customization Options for the Course

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

This guided, live training session (available online or on-site) is designed for executive participants seeking to comprehend the global 6G landscape, evaluate its commercial potential, and schedule initial strategic investments.

Upon completing this course, participants will acquire the necessary insights to:

• Recognize emerging market trends and global initiatives influencing the 6G ecosystem.
• Comprehend regulatory frameworks and spectrum allocation schedules associated with IMT-2030.
• Assess the changing vendor market and technology maturity levels.
• Formulate a roadmap for early investment, research alliances, and pilot projects.

The course on AI and Digital Twins in 6G Networks provides an in-depth exploration of how digital twin technology and AI-native optimization converge to model, simulate, and manage next-generation 6G infrastructures.

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

After completing this training, participants will be able to:

• Describe the role and architecture of digital twins within the lifecycle of 6G networks.
• Construct 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 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 government. The generation of government data and the pace of digital archiving are accelerating, driven by the surge in mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information becomes more expansive and complex, managing, processing, storing, securing, and disposing of this data grows increasingly difficult. New tools for capturing, searching, discovering, and analyzing data are enabling organizations to extract valuable insights from their unstructured data. The government sector is reaching a critical juncture, recognizing information as a strategic asset. Government bodies must protect, leverage, and analyze both structured and unstructured information to better serve the public and fulfill mission requirements. As government leaders work to transform into data-driven organizations to successfully achieve their missions, they are establishing the framework to correlate dependencies across events, people, processes, and information.

High-value government solutions will emerge from a combination of the most disruptive 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 entities 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 this requires more than simply accumulating massive quantities 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 moved to assist 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 required to analyze it.

The challenges posed by Big Data are nearly as formidable as its promise is encouraging. Efficiently storing data is one such challenge. Budgets are always tight, so agencies must minimize the cost per megabyte of storage while keeping data readily accessible so users can retrieve it when and how they need it. Backing up massive amounts of data further intensifies this challenge.

Effectively analyzing the data is another major hurdle. Many agencies utilize commercial tools that allow them to sift through vast amounts of data, identifying trends that improve operational efficiency. (A recent MeriTalk study found that federal IT executives believe Big Data could help agencies save more than $500 billion while also meeting mission objectives.)

Custom-developed Big Data tools are also enabling agencies to address 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 more routine tasks, such as sifting through resumes to match job candidates with hiring managers.

This instructor-led, live training in Norway (online or onsite) targets intermediate-level IT professionals and business managers who want to understand how IoT and edge computing can foster efficiency, real-time processing, and innovation across different industries.

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

• Understand the core principles of IoT and edge computing and their part in digital transformation.
• Identify practical applications for IoT and edge computing in manufacturing, logistics, and energy.
• Differentiate between edge and cloud computing architectures and deployment contexts.
• Implement edge computing solutions to facilitate predictive maintenance and real-time decision-making.

This instructor-led, live training in Norway (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 devices engineered to execute specific tasks within larger frameworks. The Internet of Things (IoT) refers to a vast network of physical devices equipped with sensors and software, enabling them to connect and share data across the internet.

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

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

• Gaining insight into the architecture and components of embedded systems.
• Writing and compiling C code to facilitate hardware interaction.
• Utilizing microcontroller peripherals, including timers and ADCs.
• Comprehending the role of embedded systems within IoT architectures.

Course Format

• Engaging lectures and discussions.
• Extensive exercises and practical sessions.
• Practical implementation within a live-lab environment.

Options for Customizing the Course

• To arrange a tailored training session for this course, please get in touch with us.

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

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

After completing this training, participants will be able to:

• Describe 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 enabled by 6G.
• Understand spectrum, regulatory, and policy considerations for 6G adoption.
• Draft a high-level 6G readiness roadmap for their organization.

Course Format

• 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.

This instructor-led, live training in Norway (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 Norway, participants will learn how to maximize Nginx's performance by setting up, configuring, monitoring, and troubleshooting it to handle various forms of HTTP and TCP traffic. Topics include configuring critical Nginx parameters and optimizing the operating system and virtual machine to extract maximum value from Nginx.

This instructor-led, live training in Norway (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.