6G and IoT Training Course

This training aims to clarify what 5G networks are and how they influence smart technologies. We will explore both the benefits and limitations of the synergy between 5G and IoT, while outlining the developmental trajectory of a network designed from the outset for the smart world.

This forward-thinking course delves into how 6G wireless technology converges with edge computing, IoT ecosystems, and AI-powered data processing to build intelligent, low-latency, and adaptive infrastructures.

Delivered via live, instructor-led sessions (available online or onsite), this program is designed for intermediate-level IT architects seeking to grasp and architect next-generation distributed systems by harnessing the combined power of 6G connectivity and intelligent edge platforms.

After completing this course, participants will be equipped to:

• Grasp how 6G will reshape edge computing and IoT architectures.
• Architect distributed systems capable of ultra-low latency, high bandwidth, and autonomous functions.
• Implement AI and data analytics at the edge to enable smart decision-making.
• Develop scalable, secure, and resilient 6G-ready edge infrastructures.
• Assess business and operational models that arise from the convergence of 6G and edge networks.

Course Format

• Interactive lectures and group discussions.
• Case studies and hands-on architecture design exercises.
• Practical simulations using optional edge or container-based tools.

Customization Options

• For tailored training arrangements for this course, please reach out to us.

Infrastructure and Network Design Prepared for 6G is a specialized training programme dedicated to equipping existing telecom and enterprise networks for the forthcoming era of wireless connectivity through sophisticated architectural and engineering methodologies. The curriculum encompasses the evolution of transport and fronthaul networks, cloud-native and Open RAN methodologies, edge and distributed computing, timing and synchronization protocols, spectrum and RF preparedness, automation and AI-driven operations, alongside practical migration strategies for operators and enterprises.

This instructor-led, live training (available online or onsite) targets intermediate-level telecom engineers and network architects who aim to design, optimize, and evolve their current 4G/5G infrastructure to satisfy the performance, scalability, and reliability demands of 6G.

Upon completing this course, participants will be capable of:

• Evaluating current network infrastructure deficiencies and assessing readiness for 6G evolution.
• Designing transport and fronthaul/backhaul architectures tailored for ultra-low latency and high throughput.
• Implementing cloud-native principles, vRAN/O-RAN integration, and edge compute placement for 6G use cases.
• Planning the timing, synchronization, and RF upgrades necessary for mmWave/THz and dense deployments.
• Establishing testing, validation, and operational monitoring strategies to guarantee performance and reliability.
• Developing a phased migration and investment roadmap aligned with business priorities and risk management.

Course Format

• Technical lectures and deep dives into architecture.
• Case studies and design workshops.
• Practical labs utilizing simulation and verification tools.

Course Customization Options

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

This guided, live training session (available online or on-site) is designed for executive participants aiming to comprehend the worldwide 6G context, evaluate its commercial prospects, and strategize early strategic commitments.

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

• Recognize emerging market tendencies and international efforts influencing the 6G environment.
• Comprehend regulatory frameworks and spectrum assignment schedules associated with IMT-2030.
• Assess the changing vendor environment and technological preparedness stages.
• Formulate a plan for early funding, research collaborations, and pilot projects.

The course 'AI and Digital Twins in 6G Networks' is an advanced, specialized program that investigates how AI-native optimization and digital twin technology converge to model, simulate, and manage next-generation 6G infrastructure.

This instructor-led live training, available either online or onsite, is designed for senior professionals who aim to apply digital twin methodologies and AI techniques to design, validate, and optimize 6G network behavior within realistic and reproducible environments.

Upon completing this training, participants will be able to:

• Describe the role and architecture of digital twins throughout the 6G network lifecycle.
• Construct and configure digital twin models for RAN, transport, and edge computing 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.

Course Format

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

Customization Options

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

Technological advancements and the exponential growth of data are reshaping business operations across numerous sectors, including government. The volume of data generated and archived digitally by government entities is surging, driven by the proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information expands and grows more complex, the challenges associated with its management, processing, storage, security, and disposition intensify. New 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 information as a strategic asset. Governments must now protect, leverage, and analyze both structured and unstructured data to better fulfill mission requirements. As leaders work to evolve data-driven organizations, they are establishing the framework to correlate dependencies among events, people, processes, and information.

High-impact government solutions are emerging from the integration of disruptive technologies:

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

Big Data serves as an intelligent industry solution, empowering governments to make superior decisions by acting on patterns revealed through the analysis of vast volumes of data—both related and unrelated, structured and unstructured.

However, achieving these outcomes requires more than merely accumulating large datasets. "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," noted 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 advanced this effort by launching the National Big Data Research and Development Initiative in 2012. This initiative allocated over $200 million to capitalize on the Big Data explosion and the tools necessary to analyze it.

The challenges posed by Big Data are as formidable as its potential is promising. Efficient data storage is a primary concern. With budgets often constrained, agencies must minimize the cost per megabyte of storage while ensuring data remains easily accessible for users when and how they need it. Backing up massive data volumes further complicates this challenge.

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

Custom-developed Big Data tools are also enabling agencies to meet their analytical needs. For instance, 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 applied to routine tasks, such as screening resumes to match candidates with hiring managers.

Insurtech (also known as Digital Insurance) represents the intersection of insurance and emerging technologies. Within this domain, "digital insurers" leverage technological innovations to transform their business and operational models, aiming to reduce costs, enhance customer experience, and increase operational agility.

Through this instructor-led training, participants will gain a comprehensive understanding of the technologies, methodologies, and mindset required to drive digital transformation within their organizations and across the broader industry. The course is designed for managers who seek a holistic understanding of the field, wish to cut through the hype and jargon, and are ready to take initial steps toward establishing a robust Insurtech strategy.

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

• Discuss Insurtech and its various components with intelligence and systematic clarity
• Identify and demystify the role of each key technology within the Insurtech ecosystem
• Draft a general strategy for implementing Insurtech initiatives within their organization

Audience

• Insurance professionals
• Technologists within the insurance industry
• Insurance stakeholders
• Consultants and business analysts

Format of the course

• A blend of lectures, discussions, exercises, and group case study activities

This instructor-led live training in Sweden (online or onsite) is designed for intermediate IT professionals and business managers seeking to understand how IoT and edge computing can drive efficiency, real-time processing, and innovation across various industries.

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

• Comprehend 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 Sweden (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 Sweden (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.

Embedded systems are specialized computing environments engineered to execute specific tasks within broader apparatuses. The Internet of Things (IoT) represents a vast network of connected physical devices, equipped with sensors and software, enabling them to communicate and exchange information via the internet.

This instructor-led live training (available online or on-site) targets technical professionals at the beginner level who seek 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:

• Comprehending the structure and constituent parts of embedded systems.
• Writing and compiling C code to facilitate interaction with embedded hardware.
• Utilizing microcontroller peripherals, including timers and ADCs.
• Grasping the role of embedded systems within IoT architectures.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practice sessions.
• Practical implementation in a live laboratory environment.

Customization Options for the Course

• For requests regarding customized training for this course, please get in touch with us to make arrangements.

This instructor-led, live training in Sweden (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 fundamental 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 within edge computing environments.
• Navigate challenges associated with data privacy and network limitations in IoT systems.

6G represents the next-generation wireless networking paradigm, building upon 5G advancements to enable ultra-low latency, extremely high throughput, pervasive intelligence, and integrated sensing capabilities for new classes of applications and services.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to understand the technical foundations, regulatory landscape, and strategic business impacts of 6G for planning and decision-making.

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

• Explain 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 that 6G will enable.
• Understand spectrum, regulatory, and policy considerations for 6G adoption.
• Draft a high-level 6G readiness roadmap for their organization.

Format of the Course

• 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.

In this instructor-led live training in Sweden, participants will explore the various facets of NB-IoT (also known as LTE Cat NB1) while developing and deploying 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 understand how they integrate to form a cohesive ecosystem.
• Understand and explain the security features embedded within NB-IoT devices.
• Develop a simple application for tracking NB-IoT devices.

ThingsBoard is an open-source IoT platform designed to handle device management, data collection, processing, and visualization for your IoT solutions.

During this instructor-led live training, participants will discover how to seamlessly integrate ThingsBoard into their IoT ecosystems.

Upon completing this course, participants will be capable of:

• Installing and setting up ThingsBoard
• Grasping the core features and architectural principles of ThingsBoard
• Developing IoT applications using ThingsBoard
• Connecting ThingsBoard with Kafka to route telemetry data from devices
• Leveraging Apache Spark with ThingsBoard to aggregate data across multiple devices

Target Audience

• Software Engineers
• Hardware Engineers
• Developers

Course Format

• A blend of lectures, discussions, practical exercises, and extensive hands-on practice

Important Note

• For customized training arrangements, please reach out to us directly.