6G and IoT Training Course

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. This combination supports intelligent, low-latency, and adaptive infrastructures.

This instructor-led, live training (available both online and onsite) is designed for intermediate-level IT architects who are interested in understanding and designing next-generation distributed architectures that leverage the synergy between 6G connectivity and intelligent edge systems.

Upon completing this course, participants will be able to:

• Understand how 6G will revolutionize edge computing and IoT architectures.
• Design distributed systems that ensure ultra-low latency, high bandwidth, and autonomous operations.
• Integrate AI and data analytics at the edge to facilitate intelligent decision-making.
• Plan scalable, secure, and resilient 6G-ready edge infrastructures.
• Evaluate business and operational models that are enabled by the convergence of 6G and edge technologies.

Format of the Course

• Interactive lectures and discussions.
• Case studies and practical architecture design exercises.
• Hands-on simulations with optional edge or container tools.

Course Customization Options

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

6G-Ready Infrastructure and Network Design is a specialized training program aimed at preparing existing telecom and enterprise networks for the next generation of wireless connectivity through advanced architectural and engineering practices. The program covers the evolution of transport and fronthaul, cloud-native and open RAN approaches, edge and distributed computing, timing and synchronization, spectrum and RF readiness, automation, and AI-driven operations, as well as practical migration strategies for operators and enterprises.

This instructor-led, live training (available online or on-site) is designed for intermediate-level telecom engineers and network architects who wish 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 the gaps in their current network infrastructure and assess its readiness for 6G evolution.
• Design transport and fronthaul/backhaul architectures that support ultra-low latency and high throughput.
• Implement cloud-native principles, vRAN/O-RAN integration, and edge compute placement for 6G use cases.
• Plan the necessary upgrades for timing, synchronization, and RF to accommodate mmWave/THz and dense deployments.
• Define testing, validation, and operational monitoring strategies to ensure performance and reliability.
• Develop a phased migration and investment roadmap that aligns with business priorities and risk management.

Format of the Course

• Technical lectures and in-depth architecture discussions.
• 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 instructor-led, live training (online or onsite) is aimed at executive-level participants who wish to understand the global 6G landscape, assess its business 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.

AI and Digital Twins in 6G Networks is an advanced, specialized course that delves into the integration of digital twin technology and AI-native optimization to model, simulate, and operate next-generation 6G infrastructures.

This instructor-led, live training (available online or on-site) is designed for advanced-level professionals who wish to apply digital twin methodologies and AI techniques to design, validate, and optimize the behavior of 6G networks in realistic, reproducible environments.

Upon completing this training, participants will be able to:

• Understand the role and architecture of digital twins throughout 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 facilitate model-driven orchestration and intent-based control.
• Develop validation and verification workflows using co-simulation, emulation, and digital twin testbeds.

Format of the Course

• Technical lectures and in-depth architecture discussions.
• Hands-on labs with simulators, twin models, and ML toolchains.
• Case study reviews and a practical mini-project integration exercise.

Course Customization Options

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

Advances in technology and the growing volume of information are reshaping business practices across various sectors, including government. The rapid expansion of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals has led to a significant increase in data generation and digital archiving by government entities. As the amount and complexity of digital information grow, the challenges related to managing, processing, storing, securing, and disposing of this data also become more intricate. New tools for capturing, searching, discovering, and analyzing unstructured data are enabling organizations to derive valuable insights. The government sector is at a critical juncture, recognizing that information is a strategic asset and that it must protect, leverage, and analyze both structured and unstructured data to better serve its mission requirements. Government leaders are working to transform their organizations into data-driven entities, laying the foundation to understand the interdependencies among 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 is one of the intelligent industry solutions that enable government to make better decisions by acting on patterns revealed through the analysis of large volumes of data—whether structured or unstructured, related or unrelated.

Achieving these goals requires more than just amassing vast amounts of data. "To make sense of these large volumes of Big Data, cutting-edge tools and technologies are necessary to analyze and extract useful insights from diverse streams of information," according to 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 to help agencies find these technologies by establishing the National Big Data Research and Development Initiative in 2012. This initiative allocated over $200 million to capitalize on the surge in Big Data and the tools needed for its analysis.

The challenges posed by Big Data are as formidable as its potential is promising. Efficient data storage is one of these challenges. Given tight budgets, agencies must minimize the cost per megabyte of storage while ensuring easy access to the data so that users can retrieve it quickly and in the format they need. Backing up large volumes of data further complicates this challenge.

Effective data analysis is another major hurdle. Many agencies use commercial tools to sift through vast amounts of data, identifying trends that can enhance operational efficiency. A recent study by MeriTalk found that federal IT executives believe Big Data could help agencies save more than $500 billion while also achieving their mission objectives.

Custom-developed Big Data tools are also assisting agencies in analyzing their data. 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 aided medical researchers in discovering a link that can alert doctors to aortic aneurysms before they occur. It is also used for more routine tasks, such as screening resumes to connect job candidates with hiring managers.

Insurtech, also known as Digital Insurance, represents the integration of insurance with cutting-edge technologies. In this field, "digital insurers" leverage technological innovations to optimize their business and operational models, aiming to reduce costs, enhance customer experiences, and increase operational agility.

This instructor-led training is designed to provide participants with a comprehensive understanding of the technologies, methods, and mindset required for digital transformation within their organizations and across the industry. The course is specifically targeted at managers who need to grasp the broader picture, demystify the hype and technical jargon, and take initial steps in formulating an Insurtech strategy.

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

• Discuss Insurtech and its various components with intelligence and a systematic approach.
• Identify and clarify the role of each key technology within Insurtech.
• Develop a general strategy for implementing Insurtech within their organization.

Audience

• Insurers
• Technologists in the insurance sector
• Insurance stakeholders
• Consultants and business analysts

Format of the course

• A combination of lectures, discussions, exercises, and group activities based on case studies.

This instructor-led, live training in Norway (online or onsite) is aimed 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 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 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.

This instructor-led, live training in Norway (online or onsite) is aimed at product managers and developers who wish to use Edge Computing to decentralize data management for faster performance, leveraging smart devices located on the source network.

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

• Understand the basic concepts and advantages of Edge Computing.
• Identify the use cases and examples where Edge Computing can be applied.
• Design and build Edge Computing solutions for faster data processing and reduced operational costs.

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-generation wireless networking framework that builds upon the advancements of 5G to deliver ultra-low latency, extremely high throughput, pervasive intelligence, and integrated sensing capabilities, enabling a new generation of applications and services.

This instructor-led, live training (available both online and on-site) is designed for professionals at beginner to intermediate levels who are interested in understanding the technical foundations, regulatory environment, and strategic business implications of 6G. The training aims to support planning and decision-making processes.

Upon completing this training, participants will be able to:

• Explain key 6G concepts and how they differ from those in 5G.
• Identify essential enabling technologies and their practical implications.
• Evaluate high-value use cases and industry sectors that will benefit from 6G.
• Understand the spectrum, regulatory, and policy considerations relevant to 6G adoption.
• Develop a high-level roadmap for 6G readiness within their organization.

Format of the Course

• Interactive lectures with conceptual walkthroughs.
• Case studies and sector-specific examples.
• Group workshops to create an organizational 6G readiness outline.

Course Customization Options

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

Unlike other technologies, the Internet of Things (IoT) is far more intricate, spanning virtually every core engineering discipline—mechanical, electronics, firmware, middleware, cloud, analytics, and mobile. Each layer of its engineering involves aspects of economics, standards, regulations, and the evolving state of the art. This course, for the first time, offers a comprehensive overview of all these critical aspects of IoT Engineering.

Summary

An advanced training program covering the current state of the art in Internet of Things (IoT).

This program spans multiple technology domains to develop an understanding of an IoT system and its components, as well as how it can benefit businesses and organizations.

Live demonstrations of model IoT applications will showcase practical IoT deployments across various industry sectors, including Industrial IoT, Smart Cities, Retail, Travel & Transportation, and use cases involving connected devices and things.

Target Audience

Managers responsible for business and operational processes within their organizations who want to learn how to leverage IoT to enhance the efficiency of their systems and processes.

Entrepreneurs and investors looking to create new ventures and gain a better understanding of the IoT technology landscape to effectively utilize it in their endeavors.

The market value estimates for the Internet of Things (IoT) are substantial, given that the IoT is an integrated and pervasive layer of devices, sensors, and computing power that overlays consumer, business-to-business, and government industries. The number of IoT connections is expected to grow significantly: from 1.9 billion devices today to 9 billion by 2018. That year, it will be roughly equivalent to the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

In the consumer space, many products and services have already transitioned into the IoT, including kitchen and home appliances, parking solutions, RFID, lighting and heating systems, and various applications in the Industrial Internet.

While the underlying technologies of IoT are not new—M2M communication has existed since the inception of the internet—the recent emergence of numerous inexpensive wireless technologies, coupled with the widespread adoption of smartphones and tablets in every household, has driven the current demand for IoT. The explosive growth of mobile devices has further fueled this demand.

The vast opportunities in the IoT business have attracted a significant number of small and medium-sized entrepreneurs to join the IoT gold rush. The availability of open-source electronics and IoT platforms has made the development and management of IoT systems increasingly affordable. Existing electronic product manufacturers are feeling pressure to integrate their devices with the internet or mobile apps.

This training is designed to provide a technology and business review of this emerging industry, enabling IoT enthusiasts and entrepreneurs to grasp the fundamentals of IoT technology and its business applications.

Course Objective

The main objective of the course is to introduce participants to the latest technological options, platforms, and case studies of IoT implementation in areas such as home and city automation (smart homes and cities), Industrial Internet, healthcare, government, mobile cellular networks, and more.

The course will cover a basic introduction to all elements of IoT, including mechanical components, electronics/sensor platforms, wireless and wired protocols, integration of mobile with electronics, integration of mobile with enterprise systems, data analytics, and the total control plane.

It will also delve into M2M wireless protocols for IoT, such as WiFi, Zigbee/Zwave, Bluetooth, and ANT+, discussing when and where to use each one. The program will explore mobile/desktop/web applications for registration, data acquisition, and control, including available M2M data acquisition platforms like Xively, Omega, and NovoTech.

Security issues and solutions for IoT will be addressed, along with open-source and commercial electronics platforms such as Raspberry Pi, Arduino, and ArmMbedLPC. The course will also cover open-source and commercial enterprise cloud platforms like AWS-IoT apps, Azure-IOT, Watson-IOT cloud, and other minor IoT clouds.

Finally, the course will include case studies of common IoT devices, such as home automation systems, smoke alarms, vehicles, military applications, and home health solutions.

Machine-to-Machine (M2M) involves the direct, automated exchange of information between interconnected mechanical or electronic devices.

In this instructor-led, live training in Norway, participants will learn about the various aspects of NB-IoT (also known as LTE Cat NB1) as they develop and deploy a sample NB-IoT based application.

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

• Identify the different components of NB-IoT and how to fit together to form an ecosystem.
• Understand and explain the security features built into NB-IoT devices.
• Develop a simple application to track NB-IoT devices.

ThingsBoard is an open-source IoT platform that provides device management, data collection, processing, and visualization for your IoT solution.

In this instructor-led, live training, participants will learn how to integrate ThingsBoard into their IoT solutions.

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

• Install and configure ThingsBoard
• Understand the core features and architecture of ThingsBoard
• Build IoT applications using ThingsBoard
• Integrate ThingsBoard with Kafka for telemetry data routing from devices
• Integrate ThingsBoard with Apache Spark to aggregate data from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Note

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