5G and IoT Training Course

This instructor-led live training in Slovakia (online or onsite) is designed for intermediate-level telecom professionals, AI engineers, and IoT specialists who want to explore how 5G networks accelerate 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 Slovakia (online or onsite) is designed for business managers who need to acquire the essential insights required to make informed decisions about adopting 5G. Rather than focusing on technical details, this course emphasizes the strategic thinking necessary to prepare for the 5G era. The technical and industry-specific content will be tailored to suit the audience's needs.

Upon completing this training, participants will be capable of:

• Recognizing the opportunities that 5G offers to their organization.
• Identifying the risks 5G may pose to businesses and industries.
• Comprehending and distinguishing the various technologies and standards that underpin 5G.
• Understanding the role of 5G in advancing AI and IoT.
• Leading 5G initiatives that enhance customer service and operational efficiency.
• Developing a strategy for integrating 5G products and services within the organization and among external partners.

This instructor-led, live training in Slovakia (online or onsite) targets intermediate-level professionals seeking to understand and evaluate the behavior, scope, and deployment of 5G networks in technical environments.

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

• Analyze the behavior of 5G networks in clustered environments.
• Understand the RF environment specific to 5G technology.
• Evaluate real-world cases of 5G implementation from other countries.
• Assess 5G coverage capabilities and limitations.
• Interpret and analyze 5G network quality parameters on a technical level.

This instructor-led, live training in Slovakia (online or onsite) is aimed at engineers who wish to understand the architectural components that make up 5G so as to begin implementing their own solutions on top of this groundbreaking new network.

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

• Learn the fundamentals of 5G.
• Understand the 5G architecture and standards.
• Perform network function virtualization and network slicing.

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

This instructor-led, live training (available online or onsite) targets intermediate-level IT professionals and technical managers seeking to grasp the fundamentals, architecture, and business implications of 5G networks.

Upon completing this training, participants will acquire the knowledge and skills to:

• Comprehend the core concepts and evolution of 5G technology.
• Identify the primary components and architecture of 5G networks.
• Distinguish between 4G LTE and 5G regarding performance and design.
• Evaluate 5G use cases and applications across various industries.
• Assess 5G deployment strategies and regulatory considerations.

Format of the Course

• Interactive lecture and group discussion.
• Case studies and scenario-based exercises.
• Hands-on exploration of 5G network architecture through live demonstrations.

Course Customization Options

• Upon request, this course can be tailored to focus on specific industry applications or regional 5G deployment contexts.

As the next-generation standard for wireless communication, 6G is poised to revolutionize IoT ecosystems by delivering ultra-fast connectivity, advanced sensing capabilities, and seamlessly integrated AI functions.

This instructor-led live training, available both online and onsite, is designed for advanced professionals seeking to understand and capitalize on the emerging convergence of 6G technologies and IoT applications.

Upon completing this course, learners will be equipped to:

• Articulate the fundamental technical concepts underlying 6G.
• Evaluate how 6G will transform IoT device communication and architectural frameworks.
• Analyze 6G-enabled IoT use cases across various industries.
• Develop strategies for integrating 6G capabilities into current IoT solutions.

Course Format

• Concept-driven lectures paired with expert-led discussions.
• Practical exercises designed to reinforce core engineering principles.
• Guided exploration of case studies and scenario analyses.

Customization Options

• For customized training versions aligned with your organization's technology roadmap, please contact us to arrange a session.

Technological advancements and the exponential growth of information are reshaping business operations across various sectors, including government. The volume of data generated by government entities and the rate of digital archiving are increasing rapidly, driven by the proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information expands in complexity, managing, processing, storing, securing, and disposing of it becomes increasingly challenging. New tools for capturing, searching, discovering, and analyzing data are enabling organizations to derive valuable insights from unstructured data. The government sector is at a critical juncture, recognizing information as a strategic asset. Agencies must now protect, leverage, and analyze both structured and unstructured information to better serve the public and meet mission objectives. As government leaders work to transform their organizations into data-driven entities, they are establishing the framework to correlate dependencies across events, people, processes, and information.

High-impact government solutions are emerging 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 enables governments to make better decisions by acting on patterns identified through the analysis of vast volumes of data—whether related or unrelated, structured or unstructured.

However, achieving these results requires more than just collecting 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," 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 significant steps to assist agencies in identifying these technologies by launching 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 presented by Big Data are as formidable as its promise is encouraging. Efficiently storing data is one such challenge. With budgets always under pressure, agencies must minimize storage costs per megabyte while ensuring data remains easily accessible so users can retrieve it whenever and however they need it. Backing up massive data volumes further complicates this task.

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

Custom-developed Big Data tools are also enabling agencies to address their analytical needs. For instance, 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 alert doctors to aortic aneurysms before they occur. It is also used for routine tasks, such as screening resumes to match job candidates with hiring managers.

Insurtech (also known as Digital Insurance) represents the intersection of insurance and emerging technologies. Within the Insurtech landscape, "digital insurers" leverage technological innovations to transform their business and operational models, aiming to lower costs, enhance customer experiences, and increase operational agility.

This instructor-led training helps participants understand the technologies, methodologies, and mindset required to drive digital transformation within their organizations and across the wider industry. The course is designed for managers who need a comprehensive overview, wish to cut through hype and jargon, and are ready to take initial steps toward building an Insurtech strategy.

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

• Discuss Insurtech and its various components with intelligence and systematic clarity
• Identify and clarify the role of each key technology in the Insurtech ecosystem
• Develop a general strategy for implementing Insurtech within their organization

Audience

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

Course Format

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

This instructor-led, live training in Slovakia (online or onsite) is designed for intermediate IT professionals and business managers who want 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 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 Slovakia (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 Slovakia (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 Slovakia (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.

In this instructor-led, live training in Slovakia, participants will explore the various aspects of NB-IoT (also known as LTE Cat NB1) as they develop and deploy a sample NB-IoT-based application.

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

• Identify the key components of NB-IoT and understand how they integrate to form a cohesive ecosystem.
• Understand and articulate the security features inherent in NB-IoT devices.
• Develop a basic application for tracking NB-IoT devices.

This instructor-led, live training (available online or onsite) is designed for beginner to intermediate-level telecom engineers and field professionals. The course enables participants to apply structured deployment methodologies and industry best practices to successfully install, supervise, integrate, and manage multi-vendor wireless networks from 2G to 5G within both operator and enterprise environments.

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

• Install and configure multi-vendor BTS systems (Huawei, ZTE, Ericsson) from 2G to 5G.
• Supervise site deployment activities and coordinate RF, transmission, power, civil, and core network teams during integration.
• Prepare telecom sites for ATP (Acceptance Test Procedure) and manage operator handover processes.
• Monitor wireless KPIs and manage cluster-based and region-based network operations within commercial and technical reporting structures.

ThingsBoard is an open-source IoT platform that provides 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.