5G and IoT Training Course

This instructor-led, live training in the Netherlands (online or onsite) is designed for intermediate-level telecom professionals, AI engineers, and IoT specialists looking to explore how 5G networks accelerate Edge AI applications.

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

• Understand the fundamentals of 5G technology and its impact on Edge AI.
• Deploy AI models optimized for low-latency applications in 5G environments.
• Implement real-time decision-making systems using Edge AI and 5G connectivity.
• Optimize AI workloads for efficient performance on edge devices.

This instructor-led live training in the Netherlands (online or onsite) is designed for intermediate-level professionals seeking to comprehend, assess, and implement 5G networks within technical settings.

Upon completing this training, participants will be capable of:

• Analyzing the behavior of 5G networks in clustered environments.
• Gaining insight into the RF environment specific to 5G technology.
• Evaluating practical 5G implementation cases from various countries.
• Assessing both the capabilities and limitations of 5G coverage.
• Interpreting and analyzing 5G network quality parameters at a technical level.

5G represents the fifth generation of mobile network technology, delivering faster speeds, reduced latency, and more reliable connections for a broad spectrum of applications.

This instructor-led, live training (available online or on-site) is designed for intermediate-level IT professionals and technical managers who want to gain a clear understanding of the fundamentals, architecture, and business implications of 5G networks.

Upon completing this training, participants will acquire the knowledge and skills to:

• Grasp the core concepts and evolution of 5G technology.
• Identify the primary components and architecture of 5G networks.
• Distinguish between 4G LTE and 5G in terms of performance and design.
• Evaluate 5G use cases and applications across various industries.
• Assess 5G deployment strategies and regulatory considerations.

Format of the Course

• Interactive lectures and group discussions.
• Case studies and scenario-based exercises.
• Hands-on exploration of 5G network architecture through live demonstrations.

Course Customization Options

• This course can be tailored to focus on specific industry applications or regional 5G deployment contexts upon request.

6G represents the next generation of wireless communication standards, poised to revolutionize IoT ecosystems through ultra-fast connectivity, advanced sensing capabilities, and integrated AI.

This instructor-led live training, available both online and onsite, targets advanced participants who wish to understand and leverage the emerging intersection of 6G technologies and IoT applications.

Upon completion of this course, learners will be able to:

• Explain the core technical concepts behind 6G.
• Assess how 6G will reshape IoT device communication and architecture.
• Evaluate 6G-enabled IoT use cases across industries.
• Prepare strategies for integrating 6G capabilities into existing IoT solutions.

Format of the Course

• Concept-focused lectures combined with expert discussion.
• Applied exercises designed to reinforce key engineering principles.
• Case-based exploration and scenario analysis in a guided environment.

Course Customization Options

• For tailored versions of this training aligned with your organizational technology roadmap, please contact us to arrange.

Technological advancements and the exponential growth of information are fundamentally reshaping business operations across numerous sectors, including the public sector. The volume of government data generation and digital archiving is accelerating, driven by the proliferation of mobile devices and applications, smart sensors and computing infrastructure, cloud-based solutions, and citizen-engagement portals. As digital information becomes increasingly vast and complex, the tasks of managing, processing, storing, securing, and disposing of this data become more intricate. New tools for capturing, searching, discovering, and analyzing data are empowering organizations to derive valuable insights from unstructured sources. The government sector is reaching a critical juncture, recognizing information as a strategic asset that must be protected, leveraged, and analyzed in both structured and unstructured forms to fulfill mission requirements effectively. Government leaders are working to evolve into data-driven organizations capable of successfully executing their missions, laying the groundwork to correlate dependencies among events, personnel, processes, and information.

High-value government solutions will emerge from the integration 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 agencies to make superior decisions by acting on patterns revealed through the analysis of large volumes of data—encompassing related and unrelated, as well as structured and unstructured, information.

However, achieving these capabilities requires more than simply amassing vast 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," Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy noted in a post on the OSTP Blog.

The White House supported agencies in identifying 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 develop the necessary tools for its analysis.

The challenges posed by Big Data are as significant as the opportunities it presents. Efficiently storing data is one such challenge. With budgets often constrained, agencies must minimize storage costs per megabyte while ensuring data remains readily accessible to users when and how they need it. Backing up massive data volumes further compounds this difficulty.

Effective data analysis is another major hurdle. Many agencies utilize commercial tools that allow them to navigate through large datasets, identifying trends that enhance operational efficiency. (A recent study by MeriTalk indicated 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 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 assisted medical researchers in identifying links that can alert doctors to aortic aneurysms before they occur. It is also utilized for routine tasks, such as reviewing resumes to match job candidates with hiring managers.

This instructor-led live training in the Netherlands (online or onsite) is targeted 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 across various industries.

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

• Grasping the core principles of IoT and edge computing and their significance in digital transformation.
• Recognizing use cases for IoT and edge computing within the manufacturing, logistics, and energy sectors.
• Differentiating between edge and cloud computing architectures and deployment models.
• Deploying edge computing solutions to facilitate predictive maintenance and real-time decision-making.

This instructor-led, live training in the Netherlands (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 architectures engineered to execute specific tasks within broader frameworks. The Internet of Things (IoT) represents a network of physical devices embedded with sensors and software, enabling them to communicate and exchange data via the internet.

This instructor-led live training, available online or on-site, is designed for beginner-level technical professionals seeking to comprehend and apply embedded systems and IoT principles using C programming and microcontroller architectures.

Upon completion of this training, participants will be able to:

• Comprehend the architecture and core components of embedded systems.
• Write and compile C code for interacting with embedded hardware.
• Utilize microcontroller peripherals, including timers and ADCs.
• Understand the role of embedded systems within IoT architectures.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation in a live laboratory environment.

Course Customization Options

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

This instructor-led, live training in the Netherlands (online or onsite) is designed for intermediate-level professionals who want 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.

This instructor-led, live training in the Netherlands (online or onsite) is designed for advanced-level IoT developers and smart home enthusiasts who want 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.
• Utilize IoT protocols such as MQTT and REST APIs within n8n workflows.
• Monitor, troubleshoot, and optimize IoT automation workflows.

In this instructor-led live training the Netherlands, participants will learn how to maximize Nginx's performance by setting it up, configuring it, monitoring it, and troubleshooting it to handle various types of HTTP and TCP traffic. Key topics include configuring the most critical parameters in Nginx, the operating system, and virtual machines to extract maximum value from the platform.

This instructor-led, live training (online or onsite) is aimed at beginner-level and intermediate-level telecom engineers and field professionals who wish to use structured deployment methodologies and industry best practices to successfully install, supervise, integrate, and manage multi-vendor wireless networks from 2G to 5G across operator and enterprise environments.

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

• Install and configure multi-vendor BTS systems (Huawei, ZTE, Ericsson) from 2G to 5G.
• Supervise site deployment activities and coordinate RF, transmission, power, civil, and core network teams during integration.
• Prepare telecom sites for ATP (Acceptance Test Procedure) and manage operator handover processes.
• Monitor wireless KPIs and manage cluster-based and region-based network operations within commercial and technical reporting structures.

This instructor-led, live training in the Netherlands (online or onsite) is designed for 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.