5G and IoT Training Course

This instructor-led, live training in Taiwan (online or onsite) targets intermediate-level telecom professionals, AI engineers, and IoT specialists interested in exploring how 5G networks accelerate Edge AI applications.

Upon completing this training, participants will be able to:

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

This instructor-led, live training in Taiwan (online or onsite) is designed for business managers seeking to acquire the essential insights required to make informed decisions regarding 5G adoption. Rather than a technical deep dive, this course focuses on the strategic thinking necessary to prepare for the 5G era. The technical depth and industry examples will be tailored to suit the audience's background.

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

• Recognize the opportunities 5G presents to their organization.
• Identify the risks 5G poses to business operations and the industry.
• Understand and differentiate the various technologies and standards underpinning 5G.
• Comprehend the role 5G plays in the advancement of AI and IoT.
• Lead 5G initiatives that enhance customer service and operational efficiency.
• Develop a strategy for adopting 5G products and services within the organization and among external partners.

This instructor-led, live training in Taiwan (online or in person) is designed for intermediate professionals who want to understand and evaluate the behavior, scope, and implementation of 5G networks in technical environments.

By the end 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 Taiwan (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, delivering faster speeds, reduced latency, and more reliable connections across a diverse array of applications.

This instructor-led live training (available online or onsite) is designed for intermediate-level IT professionals and technical managers who wish to understand the fundamentals, architecture, and business implications of 5G networks.

Upon completion of this training, participants will gain the knowledge and skills to:

• Understand the key concepts and evolution of 5G technology.
• Identify the main components and architecture of 5G networks.
• Recognize the differences between 4G LTE and 5G in terms of performance and design.
• Evaluate 5G use cases and applications across 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

• This course can be tailored to focus on specific industry applications or regional 5G deployment contexts upon request.

6G, the forthcoming generation of wireless communication standards, is poised to revolutionize IoT ecosystems by delivering ultra-high-speed connectivity, sophisticated sensing capabilities, and seamlessly integrated AI functionalities.

This instructor-led live training, available online or onsite, is designed for advanced participants aiming to comprehend and harness the emerging synergy between 6G technologies and IoT applications.

Upon completing this course, learners will be equipped to:

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

Course Format

• Concept-centric lectures paired with expert-led discussions.
• Practical exercises designed to reinforce core engineering principles.
• Guided case-based exploration and scenario analysis.

Course Customization Options

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

Technological advancements and the exponential growth of information are reshaping business operations across numerous sectors, including the public sector. Government agencies are generating and archiving digital records at an accelerating pace, driven by the proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information becomes more voluminous and complex, the challenges associated with information management, processing, storage, security, and retention intensify. Emerging tools for capture, search, discovery, and analysis are enabling organizations to extract valuable insights from unstructured data. The government sector has reached a critical juncture where leaders recognize information as a strategic asset. To better serve citizens and meet mission requirements, governments must protect, leverage, and analyze both structured and unstructured information. As government leaders work to evolve into data-driven organizations, they are laying the groundwork to correlate dependencies across events, people, processes, and information.

High-value government solutions are being created through the integration of disruptive technologies:

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

Big Data serves as an intelligent industry solution, enabling governments to make better decisions by acting on patterns revealed through the analysis of large volumes of data—both related and unrelated, structured and unstructured.

However, achieving these goals requires more than just accumulating massive 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 advanced this effort by establishing the National Big Data Research and Development Initiative in 2012. This initiative allocated over $200 million to maximize the potential of Big Data and the tools required to analyze it.

The challenges posed by Big Data are nearly as formidable as its promise is encouraging. Efficiently storing data is one significant challenge. With budgets remaining tight, agencies must minimize the cost per megabyte of storage while ensuring data remains easily accessible so users can retrieve it efficiently. The need to back up massive amounts of data further exacerbates this challenge.

Effectively analyzing data presents another major hurdle. Many agencies utilize commercial tools to sift through large datasets, identifying trends that improve operational efficiency. (A recent MeriTalk study found that federal IT executives believe Big Data could help agencies save over $500 billion while also fulfilling mission objectives.)

Custom-developed Big Data tools are also helping agencies meet their data analysis 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 can alert doctors to aortic aneurysms before they occur. It is also used for routine tasks, such as sifting through resumes to match job candidates with hiring managers.

This instructor-led, live training in Taiwan (online or onsite) is designed for intermediate-level IT professionals and business managers who aim to understand the potential of IoT and edge computing for driving efficiency, real-time processing, and innovation across various industries.

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

• Grasp the foundational concepts of IoT and edge computing and their significance in digital transformation.
• Identify practical use cases for IoT and edge computing in manufacturing, logistics, and energy.
• Differentiate between edge and cloud computing architectures and their deployment contexts.
• Implement edge computing solutions for predictive maintenance and real-time decision-making.

This instructor-led, live training in Taiwan (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:

• Grasp the fundamentals of Edge AI and its application in IoT.
• Establish and configure Edge AI environments for IoT devices.
• Create 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 Taiwan (online or onsite) targets product managers and developers who wish 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.

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

This instructor-led live training (available online or onsite) targets beginner-level technical professionals aiming to grasp and apply embedded systems and IoT principles using C and microcontroller architectures.

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

• Comprehend the architecture and components of embedded systems.
• Write and compile C code for interacting with embedded hardware.
• Operate microcontroller peripherals such as timers and ADCs.
• Understand the role of embedded systems within IoT architectures.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Customization Options

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

This instructor-led, live training in Taiwan (online or onsite) targets intermediate-level professionals who wish to apply Federated Learning to optimize IoT and edge computing solutions.

Upon completing this training, participants will be able to:

• Grasp the core principles and advantages of applying Federated Learning in IoT and edge contexts.
• Deploy Federated Learning models on IoT devices to enable decentralized AI processing.
• Minimize latency and enhance real-time decision-making within edge computing environments.
• Tackle challenges concerning data privacy and network limitations in IoT systems.

The Internet of Things (IoT) constitutes a network infrastructure that wirelessly links physical objects with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. Azure provides a comprehensive suite of cloud services, including an IoT Suite comprised of preconfigured solutions designed to help developers accelerate the creation of IoT projects.

In this instructor-led live training, participants will learn how to develop IoT applications using Azure.

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

• Understand the fundamentals of IoT architecture
• Install and configure Azure IoT Suite
• Learn the benefits of using Azure in programming IoT systems
• Implement various Azure IoT services (IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, IoT Device Management)
• Build, test, deploy, and troubleshoot an IoT system using Azure

Audience

• Developers
• Engineers

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.

In this instructor-led, live training in Taiwan, 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.

This instructor-led, live training (online or onsite) is aimed at beginner-level and intermediate-level telecom engineers and field professionals who wish to use 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.

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.