6G and IoT Training Course

The 6G and Intelligent Edge course offers a forward-thinking exploration of the integration between 6G wireless technologies, edge computing, IoT ecosystems, and AI-driven data processing. This course aims to support the development of intelligent, low-latency, and adaptive infrastructures.

This instructor-led, live training (available both online and on-site) is designed for intermediate-level IT architects who want to understand and design next-generation distributed architectures by leveraging the synergy between 6G connectivity and intelligent edge systems.

Upon completing this course, participants will be able to:

• Comprehend 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.
• Assess business and operational models enabled by the convergence of 6G and edge computing.

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.

The 6G-Ready Infrastructure and Network Design program is a specialized training designed to prepare existing telecom and enterprise networks for the next generation of wireless connectivity. This involves advanced architectural and engineering practices that cover transport and fronthaul evolution, cloud-native and open RAN approaches, edge and distributed computing, timing and synchronization, spectrum and RF readiness, automation, and AI-native operations. The course also includes practical migration strategies for operators and enterprises.

This live training, conducted by an instructor (either online or on-site), is tailored for intermediate-level telecom engineers and network architects who aim 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 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 to meet 6G use cases.
• Plan the necessary timing, synchronization, and RF upgrades for 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 using 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.

Delve 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 in a variety of business environments. Gain expertise in cutting-edge tools and methodologies to deploy, manage, and optimize edge computing solutions that meet specific industry needs.

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

This instructor-led, live training (available both online and onsite) is designed for advanced professionals who aim 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:

• Explain the role and architecture of digital twins throughout the lifecycle of 6G networks.
• Develop 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 support 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 in-depth architectural 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.

This instructor-led, live training in Uzbekistan (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.

Combine the transformative power of AI with the agility of edge computing in this comprehensive course. 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 to optimize 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.

This instructor-led, live training in Uzbekistan (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.

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.

This instructor-led, live training in Uzbekistan (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 paradigm that builds upon the advancements of 5G to enable ultra-low latency, extremely high throughput, pervasive intelligence, and integrated sensing capabilities, paving the way for new classes of applications and services.

This instructor-led, live training (available both online and onsite) is designed for professionals at beginner to intermediate levels who wish to grasp the technical foundations, regulatory landscape, and strategic business impacts of 6G to aid in planning and decision-making.

Upon completing this training, participants will be able to:

• Explain the core concepts of 6G and how they differ from those of 5G.
• Identify key enabling technologies and understand their practical implications.
• Evaluate high-value use cases and industry verticals that will be empowered by 6G.
• Understand the spectrum, regulatory, and policy considerations for adopting 6G.
• Develop a high-level roadmap for their organization's 6G readiness.

Format of the Course

• Interactive lectures with conceptual walkthroughs.
• Case studies and sector-specific examples.
• Group workshops to draft 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 significantly more complex, encompassing a wide range of core engineering disciplines such as Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each layer of its engineering involves various aspects of economics, standards, regulations, and the evolving state of the art. For the first time, this course offers a comprehensive overview of all these critical aspects of IoT Engineering.

Summary

An advanced training program covering the latest advancements in Internet of Things (IoT).

This program spans multiple technology domains to develop an understanding of an IoT system and its components, and 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

This course is designed for managers responsible for business and operational processes within their respective organizations who wish to learn how to leverage IoT to enhance the efficiency of their systems and processes.

It is also suitable for entrepreneurs and investors looking to build new ventures and gain a deeper understanding of the IoT technology landscape to effectively utilize it in their projects.

The market value estimates for the Internet of Things (IoT) are enormous, given that by definition, the IoT is an integrated and pervasive layer of devices, sensors, and computing power that spans consumer, business-to-business, and government industries. By 2018, the number of connected devices is expected to reach 9 billion, which will be roughly equivalent to the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

In the consumer space, numerous products and services have already integrated with the IoT, including kitchen and home appliances, parking solutions, RFID technology, 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 significant changes in recent years include the emergence of numerous inexpensive wireless technologies, coupled with the widespread adoption of smartphones and tablets. The explosive growth of mobile devices has driven the current demand for IoT.

Due to the vast opportunities in the IoT business, many small and medium-sized entrepreneurs have joined the IoT gold rush. Additionally, the rise of open-source electronics and IoT platforms has made the development and management of IoT systems more affordable. Existing electronic product owners are facing pressure to integrate their devices with the internet or mobile applications.

This training aims to provide a technology and business review of an emerging industry, enabling IoT enthusiasts and entrepreneurs to grasp the fundamentals of IoT technology and its business potential.

Course Objective

The primary goal of this course is to introduce participants to the latest technological options, platforms, and case studies of IoT implementations in areas such as home and city automation (smart homes and cities), Industrial Internet, healthcare, government, mobile cellular networks, and other sectors.

It will cover a basic introduction to all elements of IoT, including Mechanical components, Electronics/sensor platforms, Wireless and wireline protocols, Mobile-to-Electronics integration, Mobile-to-Enterprise integration, Data analytics, and Total control plane.

The course will also delve into M2M wireless protocols for IoT, such as WiFi, Zigbee/Zwave, Bluetooth, and ANT+, explaining when and where to use each one.

Participants will learn about mobile/desktop/web applications for registration, data acquisition, and control, as well as available M2M data acquisition platforms like Xively, Omega, and NovoTech.

The course will address security issues and solutions for IoT, including open-source and commercial electronics platforms such as Raspberry Pi, Arduino, and ArmMbedLPC.

It will also cover open-source and commercial enterprise cloud platforms for AWS-IoT apps, Azure-IOT, Watson-IOT cloud, and other minor IoT clouds.

Finally, the course will include studies of the business and technology behind common IoT devices like home automation systems, smoke alarms, vehicles, military applications, and home health solutions.

In this instructor-led, live training in Uzbekistan, 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 comprehensive device management, data collection, processing, and visualization capabilities for your IoT solutions.

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

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

• Install and configure ThingsBoard
• Understand the core features and architecture of ThingsBoard
• Develop IoT applications using ThingsBoard
• Integrate ThingsBoard with Kafka for efficient 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, with exercises and extensive hands-on practice

Note

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