6G and IoT Training Course

This training aims to explain the fundamentals of 5G networks and their impact on smart technologies. It highlights both the benefits and drawbacks of the relationship between these technologies (5G and IoT) and outlines the development directions of a network designed from its inception for the smart world.

This forward-looking course examines the convergence of 6G wireless technologies, edge computing, IoT ecosystems, and AI-driven data processing to build intelligent, adaptive, and low-latency infrastructures.

Designed for intermediate IT architects, this instructor-led training (available online or onsite) focuses on understanding and designing next-generation distributed architectures that leverage the combined power of 6G connectivity and intelligent edge systems.

After completing this course, participants will be able to:

• Comprehend how 6G will reshape edge computing and IoT architectures.
• Architect distributed systems optimized for ultra-low latency, high bandwidth, and autonomous operations.
• Implement AI and data analytics at the edge to enable intelligent decision-making.
• Plan scalable, secure, and resilient infrastructures ready for 6G adoption.
• Assess the business and operational models facilitated by the 6G-edge convergence.

Course Format

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

Customization Options

• To arrange customized training for this course, please contact us to discuss your specific needs.

The "6G-Ready Infrastructure and Network Design" program is a specialized training initiative designed to equip existing telecom and enterprise networks with the advanced architectural and engineering practices needed for next-generation wireless connectivity. The curriculum explores the evolution of transport and fronthaul networks, cloud-native and Open RAN methodologies, edge and distributed computing, timing and synchronization, spectrum and RF preparedness, automation, AI-native operations, and practical migration strategies tailored for operators and enterprises.

Delivered as an instructor-led, live session (available online or onsite), this course targets intermediate-level telecom engineers and network architects aiming to design, optimize, and evolve their current 4G/5G infrastructure to meet the performance, scalability, and reliability demands of 6G.

Upon completing this course, participants will be able to:

• Evaluate current network infrastructure gaps and assess readiness for 6G evolution.
• Design transport and fronthaul/backhaul architectures capable of supporting ultra-low latency and high throughput.
• Implement cloud-native principles, integrate vRAN/O-RAN, and optimize edge compute placement for 6G use cases.
• Plan necessary timing, synchronization, and RF upgrades for dense deployments utilizing mmWave/THz frequencies.
• Establish testing, validation, and operational monitoring strategies to ensure optimal performance and reliability.
• Develop a phased migration and investment roadmap that aligns with business priorities and risk management protocols.

Course Format

• Technical lectures and deep dives into network architecture.
• Case studies and collaborative design workshops.
• Hands-on labs utilizing simulation and verification tools.

Customization Options

• For customized training on this topic, please contact us to arrange a session.

This instructor-led live training, offered online or onsite, targets executive-level participants who aim to understand the global 6G landscape, assess its business potential, and plan early strategic investments.

Upon completion of this course, participants will acquire the insights necessary to:

• Recognize emerging market trends and international initiatives influencing the 6G ecosystem.
• Grasp regulatory frameworks and spectrum allocation schedules associated with IMT-2030.
• Assess the changing vendor landscape and technology readiness stages.
• Create a strategic roadmap for early investments, research collaborations, and pilot projects.

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 reshaping operational practices across numerous sectors, including government. The generation of government data and the rates of digital archiving are climbing, driven by the rapid expansion 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 also become more intricate. New tools for capture, search, discovery, and analysis are enabling organizations to derive meaningful insights from unstructured data. The government sector is reaching a critical juncture, recognizing information as a strategic asset. To better serve the public and fulfill mission requirements, governments must protect, leverage, and analyze both structured and unstructured information. As government leaders strive to evolve their organizations into data-driven entities, they are establishing the foundation to correlate dependencies among events, personnel, processes, and information.

High-value government solutions will emerge from the integration of several disruptive technologies:

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

Big Data represents a transformative industry solution that empowers government agencies to make superior decisions by acting on patterns revealed through the analysis of vast volumes of data—whether related or unrelated, structured or unstructured.

However, achieving these outcomes requires more than merely accumulating large 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," wrote 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 toward assisting 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 the tools necessary to analyze it.

The challenges posed by Big Data are nearly as daunting as the promise it offers is encouraging. Efficient data storage is one such challenge. With budgets remaining tight, agencies must minimize the per-megabyte cost of storage while ensuring data remains easily accessible, allowing users to retrieve information when and how they need it. Backing up massive quantities of data further intensifies this challenge.

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

Custom-developed Big Data tools are also enabling 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 can alert doctors to aortic aneurysms before they occur. It is also employed for routine tasks, such as screening resumes to connect job candidates with hiring managers.

Insurtech, also known as Digital Insurance, represents the intersection of the insurance industry and emerging technologies. Within this sector, digital insurers leverage technological innovations to revolutionize their business and operational models, aiming to lower costs, elevate the customer experience, and increase operational agility.

This instructor-led training enables participants to grasp the technologies, methodologies, and mindset required to drive digital transformation within their organizations and across the broader industry. The course is designed for managers seeking a comprehensive overview, helping them cut through industry hype and jargon to take initial steps toward developing an effective Insurtech strategy.

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

• Discuss Insurtech and its various components with intelligence and structure.
• Identify and demystify the role of key technologies within the Insurtech landscape.
• Draft a foundational strategy for implementing Insurtech within their organization.

Target Audience

• Insurance providers
• Technologists working within the insurance sector
• Stakeholders in the insurance industry
• Consultants and business analysts

Course Format

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

This instructor-led, live training in Turkey (online or onsite) is designed for intermediate-level 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:

• Understand the core 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 Turkey (online or onsite) is tailored for intermediate-level developers, system architects, and industry professionals seeking to leverage Edge AI to enhance IoT applications with intelligent data processing and analytics capabilities.

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

• Grasping the fundamentals of Edge AI and its role in IoT.
• Setting up and configuring Edge AI environments for IoT devices.
• Developing and deploying AI models on edge devices for IoT solutions.
• Implementing real-time data processing and decision-making capabilities in IoT systems.
• Integrating Edge AI with various IoT protocols and platforms.
• Addressing ethical considerations and adhering to best practices for Edge AI in IoT.

This instructor-led, live training in Turkey (online or onsite) is designed for product managers and developers who aim to decentralize data management for improved performance by leveraging smart devices 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 platforms engineered to execute specific tasks within broader operational frameworks. The Internet of Things (IoT) refers to a vast network of physical devices equipped with sensors and software, enabling them to communicate and share data via the internet.

This instructor-led live training, available either online or onsite, targets technical professionals at the beginner level who aim to grasp and apply concepts related to embedded systems and IoT using C programming and microcontroller architectures.

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

• Comprehend the architecture and core components of embedded systems.
• Write and compile C code to facilitate interaction 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.
• Numerous exercises and practical sessions.
• Hands-on implementation in a live laboratory environment.

Customization Options

• For requests regarding customized training for this course, please contact us to make arrangements.

This instructor-led, live training in Turkey (online or onsite) is designed for intermediate-level professionals aiming to apply Federated Learning to optimize IoT and edge computing solutions.

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

• Grasp the principles and advantages of applying 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 within edge computing environments.
• Overcome challenges associated with data privacy and network limitations in IoT systems.

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

This instructor-led live training, available online or onsite, is designed for beginner to intermediate professionals seeking to understand the technical foundations, regulatory landscape, and strategic business implications of 6G for effective planning and decision-making.

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

• Explain core 6G concepts and distinguish them from 5G.
• Identify key enabling technologies and their practical implications.
• Assess high-value use cases and industry verticals enabled by 6G.
• 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 Turkey, participants will explore various aspects 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 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 designed for device management, data collection, processing, and visualization for your IoT solutions.

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 fundamentals of ThingsBoard features and architecture
• Build IoT applications with ThingsBoard
• Integrate ThingsBoard with Kafka for telemetry device data routing
• Integrate ThingsBoard with Apache Spark for data aggregation from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

Format of the course

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

Note

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