6G and IoT Training Course

This training aims to clarify what 5G networks are and their influence on smart technologies. We will explore both the advantages and disadvantages of the relationship between these technologies (5G/IoT), as well as the developmental trajectories of networks originally designed for the smart world.

6G and the Intelligent Edge is a forward-looking course that explores 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:

• Understand 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 6G-Ready Infrastructure and Network Design program is a specialized training initiative aimed at transforming existing telecommunications and enterprise networks to support the forthcoming era of wireless connectivity. By leveraging advanced architectural frameworks and engineering methodologies, the course addresses critical areas such as transport and fronthaul evolution, cloud-native and Open RAN architectures, edge and distributed computing, precise timing and synchronization, spectrum and RF readiness, as well as automation and AI-driven operations. It also provides practical strategies for migration tailored to operators and enterprises.

Delivered through live, instructor-led sessions (available online or on-site), this training is designed for intermediate-level telecom engineers and network architects who seek to design, optimize, and evolve their current 4G/5G infrastructure to satisfy the performance, scalability, and reliability demands of 6G.

After completing this course, participants will be capable of:

• Evaluating existing network infrastructure to identify gaps and assess readiness for 6G evolution.
• Architecting transport and fronthaul/backhaul solutions tailored for ultra-low latency and high throughput.
• Implementing cloud-native principles, integrating vRAN/O-RAN, and optimizing edge compute placement for 6G applications.
• Strategizing timing, synchronization, and RF enhancements necessary for mmWave/THz technologies and dense network deployments.
• Establishing testing, validation, and operational monitoring protocols to guarantee performance and reliability.
• Crafting phased migration and investment roadmaps that align with business objectives and risk management frameworks.

Course Format

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

Customization Options

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

This instructor-led, live training (available online or onsite) targets executive-level professionals aiming to grasp the global 6G landscape, evaluate its commercial potential, and strategize early strategic investments.

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

• Spot emerging market trends and global initiatives influencing the 6G ecosystem.
• Comprehend regulatory frameworks and spectrum allocation schedules concerning IMT-2030.
• Assess the shifting vendor landscape and technology readiness stages.
• Formulate a roadmap for early investment, research collaborations, and pilot projects.

Dive deeper into the innovative realm of edge computing with this advanced course. Explore sophisticated architectures and tackle integration challenges, preparing to leverage the full potential of edge computing across diverse business environments. Gain expertise in cutting-edge tools and methodologies to deploy, manage, and optimize edge computing solutions that meet specific industry needs.

AI and Digital Twins in 6G Networks is an advanced, specialized course that explores how digital twin technology and AI-native optimization converge to model, simulate, and operate next-generation 6G infrastructures.

This instructor-led, live training (online or onsite) is aimed at advanced-level professionals who wish to apply digital twin methodologies and AI techniques to design, validate, and optimize 6G network behavior in realistic, reproducible environments.

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

• Explain the role and architecture of digital twins in the lifecycle of 6G networks.
• Build and configure digital twin models for RAN, transport, and edge compute components.
• Apply 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 fundamentally transforming business operations across various sectors, including government. The volume of government data and digital archiving is increasing rapidly, driven by the proliferation of mobile devices and applications, smart sensors and IoT devices, cloud computing solutions, and citizen-facing portals. As digital information becomes more expansive and complex, the management, processing, storage, security, and disposition of this data become increasingly challenging. New tools for capture, search, discovery, and analysis are enabling organizations to extract valuable insights from unstructured data. The government sector is at a critical tipping point, recognizing information as a strategic asset. Governments must now protect, leverage, and analyze both structured and unstructured data to better serve the public and meet mission requirements. As government leaders work to evolve into data-driven organizations, they are establishing the foundation to correlate dependencies across events, people, processes, and information.

High-impact 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 a key intelligent industry solution, enabling governments to make better decisions by acting on patterns revealed through the analysis of large volumes of related and unrelated, structured and unstructured data.

However, achieving these outcomes requires more than just accumulating massive amounts 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," noted Tom Kalil and Fen Zhao from 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 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 necessary analytical tools.

The challenges posed by Big Data are nearly as formidable as the promise it offers. One major challenge is efficient data storage. With budgets often tight, agencies must minimize storage costs per megabyte while ensuring data remains easily accessible for users to retrieve when and how they need it. Backing up such massive data volumes adds another layer of complexity.

Effective data analysis presents another significant challenge. Many agencies utilize commercial tools to sift through vast amounts of data, 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 fulfilling mission objectives.

Custom-developed Big Data tools are also empowering agencies to meet their analytical 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 assisted medical researchers in identifying links that alert doctors to aortic aneurysms before they occur. It is also employed for more routine tasks, such as screening resumes to match job candidates with hiring managers.

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

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

• Understand the core principles of IoT and edge computing and their role in digital transformation.
• Identify use cases for IoT and edge computing in the 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.

In this comprehensive course, combine the transformative potential of AI with the agility of edge computing. Learn to deploy AI models directly on edge devices, from understanding CNN architectures to mastering knowledge distillation and federated learning. This hands-on training will equip you with the skills needed to optimise AI performance for real-time processing and decision-making at the edge.

This instructor-led, live training in Uzbekistan (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.

Build a strong foundation in designing and managing a resilient edge computing infrastructure. Learn about open hybrid cloud infrastructures, managing workloads across diverse clouds, and ensuring flexibility and redundancy. This training provides essential knowledge on creating a scalable and secure infrastructure that supports the dynamic needs of modern applications with edge computing.

Embedded systems are specialized computing platforms engineered to execute specific tasks within broader systems. IoT (Internet of Things) refers to a network of physical devices equipped with sensors and software, enabling them to communicate and share data over the internet.

This instructor-led, live training (available online or onsite) is designed for beginner-level technical professionals seeking to understand and apply embedded systems and IoT concepts using C and microcontroller architectures.

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

• Grasp the architecture and components of embedded systems.
• Write and compile C code for interacting with embedded hardware.
• Utilize microcontroller peripherals such as timers and ADCs.
• Understand the role of embedded systems within IoT architectures.

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in Uzbekistan (available online or on-site) is designed for intermediate-level professionals seeking to leverage Federated Learning to optimize IoT and edge computing solutions.

By the conclusion 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.
• Tackle challenges related to data privacy and network constraints within IoT systems.

6G is the next-generation wireless networking paradigm that builds on 5G advances 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 (available online or on-site) is designed for beginner to intermediate-level professionals seeking to understand the technical foundations, regulatory landscape, and strategic business implications of 6G for effective planning and decision-making.

Upon completing 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 organisation.

Course Format

• Interactive lectures with conceptual walkthroughs.
• Case studies and sector-specific examples.
• Group workshop to develop an organisational 6G readiness outline.

Course Customisation Options

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

This hands-on, practical course offers a thorough introduction to the Internet of Things (IoT), spanning from device-level programming to cloud-based data processing and visualization. Participants will navigate the complete IoT architecture—including sensors, communication protocols, microcontrollers, and cloud integration—through guided exercises utilizing development boards such as ESP32 and Raspberry Pi. By the conclusion of the course, learners will be equipped to construct an end-to-end IoT pipeline: capturing sensor data, transmitting it via MQTT/HTTP, processing it on cloud platforms like Azure IoT Hub, AWS IoT Core, or Google Cloud IoT, and visualizing the results using tools such as Grafana or Power BI. The curriculum also addresses security best practices and simulated cyber threats to guarantee robust and secure deployments.