5G and IoT Training Course

This instructor-led live training in Bulgaria (online or onsite) targets intermediate-level telecom professionals, AI engineers, and IoT specialists interested in exploring the role of 5G networks in accelerating Edge AI applications.

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

• Understand the fundamentals of 5G technology and its impact on Edge AI.
• Deploy AI models optimized for low-latency applications in 5G environments.
• Implement real-time decision-making systems using Edge AI and 5G connectivity.
• Optimize AI workloads for efficient performance on edge devices.

This instructor-led, live training in Bulgaria (online or onsite) is aimed at business managers who wish to learn only the critical information needed to make important decisions about the adoption of 5G. This course is not a technical course but rather a course on the strategic thinking needed to prepare for the arrival of 5G. The technical coverage and industry coverage will be adapted to the audience.

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

• Identify the opportunities that 5G brings to the organization.
• Identify the risks that 5G poses to business and industry.
• Understand and distinguish the different technologies and standards underlying 5G.
• Understand the role that 5G will play in the further development of AI and IoT.
• Head up 5G initiatives that lead to improvements in customer service and operational efficiency.
• Initiate a strategy for adopting 5G products and services within the organization as well as across external partner organizations.

This instructor-led, live training in Bulgaria (online or onsite) is tailored for intermediate-level professionals seeking to comprehend and assess the performance, scope, and deployment of 5G networks within technical settings.

Upon completing this training, participants will be equipped to:

• Analyze the performance of 5G networks in clustered setups.
• Grasp the RF environment unique to 5G technology.
• Review real-world 5G deployment examples from various countries.
• Evaluate the coverage capabilities and constraints of 5G.
• Interpret and analyze 5G network quality parameters from a technical perspective.

5G represents the fifth generation of mobile network technology, designed to deliver faster data speeds, reduced latency, and more reliable connectivity for a diverse array of applications.

This instructor-led live training, available online or in person, is designed for intermediate-level IT professionals and technical managers seeking to grasp the fundamentals, architecture, and business impact of 5G networks.

After completing this course, participants will be able to:

• Comprehend the core concepts and historical development of 5G technology.
• Identify the primary components and architectural structure of 5G networks.
• Compare 4G LTE and 5G regarding performance capabilities and design principles.
• Explore 5G use cases and applications across various industries.
• Evaluate 5G deployment strategies and relevant regulatory factors.

Course Format

• Interactive lectures combined with group discussions.
• Case studies and scenario-based exercises.
• Practical exploration of 5G network architecture through live demonstrations.

Customization Options

• The course content can be adjusted to emphasize specific industry applications or regional 5G deployment contexts, upon request.

6G represents the next-generation wireless communication standard, poised to revolutionize IoT ecosystems through ultra-fast connectivity, advanced sensing, and integrated AI capabilities.

This instructor-led, live training (online or onsite) is designed for advanced-level participants who wish to understand and leverage the emerging intersection of 6G technologies and IoT applications.

By completing this course, learners will gain the ability to:

• Explain the core technical concepts behind 6G.
• Assess how 6G will reshape IoT device communication and architecture.
• Evaluate 6G-enabled IoT use cases across industries.
• Prepare strategies for integrating 6G capabilities into existing IoT solutions.

Format of the Course

• Concept-focused lectures combined with expert discussion.
• Applied exercises designed to reinforce key engineering principles.
• Case-based exploration and scenario analysis in a guided environment.

Course Customization Options

• For tailored versions of this training aligned with your organizational technology roadmap, please contact us to arrange.

Technological advancements and the exponential growth of information are fundamentally reshaping business operations across various sectors, including government. The generation of government data and digital archiving rates are surging, driven by the rapid proliferation of mobile devices and applications, smart sensors and IoT devices, cloud computing solutions, and citizen-facing portals. As digital information expands in volume and complexity, the challenges associated with information management, processing, storage, security, and disposition become increasingly intricate. Emerging tools for capture, search, discovery, and analysis are enabling organizations to extract valuable insights from unstructured data. The government sector is reaching a critical tipping point, recognizing that information is a strategic asset. Consequently, governments must protect, leverage, and analyze both structured and unstructured information to better fulfill mission requirements. As government leaders strive to evolve into data-driven organizations to successfully accomplish their missions, they are laying the groundwork to correlate dependencies across events, personnel, processes, and information.

High-value government solutions will emerge from a combination of the most disruptive technologies:

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

Big Data represents one of the intelligent industry solutions that enable governments to make better decisions by taking action based on patterns revealed through the analysis of large volumes of data—both related and unrelated, structured and unstructured.

However, achieving these goals requires 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," 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 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 more than $200 million to maximize the potential of the Big Data explosion and the tools required to analyze it.

The challenges posed by Big Data are nearly as daunting as its promise is encouraging. One significant challenge is efficient data storage. With budgets always tight, agencies must minimize the per-megabyte cost of storage while keeping data easily accessible so users can retrieve it when and how they need it. Backing up massive quantities of data further exacerbates this challenge.

Effectively analyzing data presents another major hurdle. Many agencies utilize commercial tools that allow them to sift through mountains of data, identifying trends that help them operate more efficiently. (A recent study by MeriTalk found that federal IT executives believe Big Data could help agencies save more than $500 billion while also fulfilling mission objectives.)

Custom-developed Big Data tools are also enabling agencies to address their data analysis needs. For example, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. This system has helped medical researchers identify links that can alert doctors to aortic aneurysms before they occur. It is also used for more routine tasks, such as sifting through resumes to connect job candidates with hiring managers.

This instructor-led, live training in Bulgaria (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 completing this training, participants will be able to:

• Comprehend the core principles of IoT and edge computing and their significance in digital transformation.
• Recognize specific use cases for IoT and edge computing within the manufacturing, logistics, and energy industries.
• Distinguish between edge and cloud computing architectures, as well as their respective deployment scenarios.
• Deploy edge computing solutions to support predictive maintenance and real-time decision-making processes.

This instructor-led, live training in Bulgaria (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 Bulgaria (online or onsite) is designed for product managers and developers who aim to utilize Edge Computing to decentralize data management for improved performance, capitalizing on smart devices situated at the source network.

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

• Understand the core concepts and advantages of Edge Computing.
• Identify use cases and examples suitable for Edge Computing application.
• Design and build Edge Computing solutions to facilitate faster data processing and lower operational costs.

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

This instructor-led training session, available both online and onsite, is tailored for entry-level technical professionals eager to grasp and implement embedded systems and IoT principles using C programming and microcontroller architectures.

Upon completing this training, participants will be capable of:

• Gaining a thorough understanding of embedded system architecture and its constituent parts.
• Writing and compiling C code to facilitate interaction with embedded hardware.
• Operating microcontroller peripherals, including timers and ADCs.
• Comprehending the role embedded systems play within IoT architectures.

Course Format

• Engaging lectures and group discussions.
• Extensive practical exercises and hands-on practice.
• Live-lab implementation exercises.

Customization Options

• For tailored training on this subject, please reach out to us to make arrangements.

This instructor-led, live training in Bulgaria (online or onsite) is tailored for 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.

The Internet of Things (IoT) constitutes a network infrastructure that wirelessly links physical objects and software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. C is a general-purpose programming language widely recommended for IoT development due to its pervasive use and advantages in low-level programming.

Through this instructor-led live training, participants will acquire the skills necessary to develop IoT solutions using C.

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

• Install and configure NetBeans for programming IoT systems with C
• Comprehend the fundamentals of IoT architecture
• Recognize the benefits of utilizing C in IoT programming
• Build, test, deploy, and troubleshoot an IoT system using C

Audience

• Developers
• Engineers

Format of the course

• A combination of lectures, discussions, exercises, and intensive hands-on practice

Note

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

This hands-on 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 examine the entire IoT architecture—including sensors, communication protocols, microcontrollers, and cloud integration—through guided exercises utilizing development boards such as ESP32 and Raspberry Pi. Upon completing the course, learners will be equipped to construct a full 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 it using tools such as Grafana or Power BI. The curriculum also addresses security best practices and simulated cyber threats to guarantee secure and robust deployments.

The Internet of Things (IoT) constitutes a network infrastructure that wirelessly links physical devices with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture mechanisms. Java, a versatile programming language renowned for its 'write once, run anywhere' capability, is highly recommended for IoT development due to its efficiency and portability.

During this instructor-led live training, participants will acquire the skills necessary to develop IoT solutions using Java.

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

• Install and configure the necessary tools and frameworks (such as the Eclipse Open IoT Stack) for building Java-based IoT systems
• Grasp the core principles of IoT architecture
• Utilize the Eclipse Open IoT Stack for Java to connect and manage devices within an IoT environment
• Construct, test, and deploy an IoT system leveraging Java

Audience

• Software Developers
• Engineers

Format of the course

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

Note

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

This instructor-led, live training (online or onsite) targets beginner to intermediate telecom engineers and field professionals seeking to leverage structured deployment methodologies and industry best practices to successfully install, supervise, integrate, and manage multi-vendor wireless networks from 2G to 5G across operator and enterprise environments.

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

• Installing and configuring multi-vendor BTS systems (Huawei, ZTE, Ericsson) from 2G to 5G.
• Supervising site deployment activities and coordinating RF, transmission, power, civil, and core network teams during integration.
• Preparing telecom sites for ATP (Acceptance Test Procedure) and managing operator handover processes.
• Monitoring wireless KPIs and managing cluster-based and region-based network operations within commercial and technical reporting structures.