6G and IoT Training Course

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.

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

This instructor-led, live training (online or onsite) is aimed at intermediate-level telecom engineers and network architects who wish to design, optimize, and evolve their current 4G/5G infrastructure to meet 6G performance, scalability, and reliability requirements.

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

• Assess current network infrastructure gaps and readiness for 6G evolution.
• Design transport and fronthaul/backhaul architectures suitable for ultra-low latency and high throughput.
• Apply cloud-native principles, vRAN/O-RAN integration, and edge compute placement for 6G use cases.
• Plan timing, synchronization, and RF upgrades required 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 aligned with business priorities and risk management.

Format of the Course

• Technical lectures and architecture deep dives.
• 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 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.

Advances in technologies and the increasing amount of information are transforming how business is conducted in many industries, including government. Government data generation and digital archiving rates are on the rise due to the rapid growth of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals. As digital information expands and becomes more complex, information management, processing, storage, security, and disposition become more complex as well. New capture, search, discovery, and analysis tools are helping organizations gain insights from their unstructured data. The government market is at a tipping point, realizing that information is a strategic asset, and government needs to protect, leverage, and analyze both structured and unstructured information to better serve and meet mission requirements. As government leaders strive to evolve data-driven organizations to successfully accomplish mission, they are laying the groundwork to correlate dependencies across events, people, processes, and information.

High-value government solutions will be created from a mashup 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 and allows government to make better decisions by taking action based on patterns revealed by analyzing large volumes of data — related and unrelated, structured and unstructured.

But accomplishing these feats takes far more than simply accumulating massive quantities 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," Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote in a post on the OSTP Blog.

The White House took a step toward helping agencies find these technologies when it established the National Big Data Research and Development Initiative in 2012. The initiative included more than $200 million to make the most of the explosion of Big Data and the tools needed to analyze it.

The challenges that Big Data poses are nearly as daunting as its promise is encouraging. Storing data efficiently is one of these challenges. As always, budgets are tight, so agencies must minimize the per-megabyte price of storage and keep the data within easy access so that users can get it when they want it and how they need it. Backing up massive quantities of data heightens the challenge.

Analyzing the data effectively is another major challenge. Many agencies employ commercial tools that enable them to sift through the mountains of data, spotting trends that can help them operate more efficiently. (A recent study by MeriTalk found that federal IT executives think Big Data could help agencies save more than $500 billion while also fulfilling mission objectives.).

Custom-developed Big Data tools also are allowing agencies to address the need to analyze their data. For example, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. The system has helped medical researchers find a link that can alert doctors to aortic aneurysms before they strike. It’s also used for more mundane tasks, such as sifting through resumes to connect job candidates with hiring managers.

This instructor-led, live training in Poland (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 Poland (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 Poland (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 Poland (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 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 (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.

Unlike other technologies, IoT is far more complex encompassing almost every branch of core Engineering-Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics and Mobile. For each of its engineering layers, there are aspects of economics, standards, regulations and evolving state of the art. This is for the firs time, a modest course is offered to cover all of these critical aspects of IoT Engineering.

Summary

An advanced training program covering the current state of the art in Internet of Things

Cuts across multiple technology domains to develop awareness of an IoT system and its components and how it can help businesses and organizations.

Live demo of model IoT applications to showcase practical IoT deployments across different industry domains, such as Industrial IoT, Smart Cities, Retail, Travel & Transportation and use cases around connected devices & things

Target Audience

Managers responsible for business and operational processes within their respective organizations and want to know how to harness IoT to make their systems and processes more efficient.

Entrepreneurs and Investors who are looking to build new ventures and want to develop a better understanding of the IoT technology landscape to see how they can leverage it in an effective manner.

Estimates for Internet of Things or IoT market value are massive, since by definition the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 1.9 billion devices today, and 9 billion by 2018. That year, it will be roughly equal to the number of smartphones, smart TVs, tablets, wearable computers, and PCs combined.

In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking, RFID, lighting and heating products, and a number of applications in Industrial Internet.

However, the underlying technologies of IoT are nothing new as M2M communication existed since the birth of Internet. However what changed in last couple of years is the emergence of number of inexpensive wireless technologies added by overwhelming adaptation of smart phones and Tablet in every home. Explosive growth of mobile devices led to present demand of IoT.

Due to unbounded opportunities in IoT business, a large number of small and medium sized entrepreneurs jumped on a bandwagon of IoT gold rush. Also due to emergence of open source electronics and IoT platform, cost of development of IoT system and further managing its sizable production is increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their device with Internet or Mobile app.

This training is intended for a technology and business review of an emerging industry so that IoT enthusiasts/entrepreneurs can grasp the basics of IoT technology and business.

Course Objective

Main objective of the course is to introduce emerging technological options, platforms and case studies of IoT implementation in home & city automation (smart homes and cities), Industrial Internet, healthcare, Govt., Mobile Cellular and other areas.

Basic introduction of all the elements of IoT-Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data-analytics and Total control plane

M2M Wireless protocols for IoT- WiFi, Zigbee/Zwave, Bluetooth, ANT+ : When and where to use which one?

Mobile/Desktop/Web app- for registration, data acquisition and control –Available M2M data acquisition platform for IoT-–Xively, Omega and NovoTech, etc.

Security issues and security solutions for IoT

Open source/commercial electronics platform for IoT-Raspberry Pi, Arduino , ArmMbedLPC etc

Open source /commercial enterprise cloud platform for AWS-IoT apps, Azure -IOT, Watson-IOT cloud in addition to other minor IoT clouds

Studies of business and technology of some of the common IoT devices like Home automation, Smoke alarm, vehicles, military, home health etc.

The Internet of Things (IoT) is a concept in which everyday devices are connected to each other and to the Internet, which allows them to collect, exchange and analyze data. - IoT devices can be diverse: from smartphones, watches, medical devices, to cars, home appliances and industrial sensors. - These devices are connected using various technologies, such as Wi-Fi, Bluetooth, Zigbee, LTE and cellular networks, which enable them to communicate with each other and with Internet networks. - Equipped with sensors, IoT devices can collect data from the environment, e.g. temperature, humidity, geographical location, biometric data, etc. - The collected data is sent to the cloud or local data centers, where it is analyzed and processed into useful information. - Based on the collected data, devices can perform tasks automatically, e.g. regulate temperature, monitor health, control home systems, etc. - In industry, IoT can be used to monitor and optimize production processes, inventory management, monitor machine performance, etc. - In business IoT can help deliver services, personalize customer experiences, supply chain management, etc. - IoT is constantly evolving, integrating with artificial intelligence, machine learning and new technologies, which opens the door to new applications and innovations. The Internet of Things is changing the way we connect with the world, enabling us to monitor, control and optimize various aspects of our everyday lives, work and industry. Its development brings many new opportunities and challenges, especially related to security, privacy and data management.

Machine-to-Machine (M2M) refers to direct automated communication between networked mechanical or electronic devices.

In this instructor-led, live training in Poland, 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 offers 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 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.