Introduction to IoT Using Raspberry Pi Training Course

The objective of this training is to clarify the nature of 5G networks and their impact on smart technologies. We aim to demonstrate both the advantages and disadvantages of the relationship between these technologies (5G and IoT), while highlighting the developmental trajectory of a network designed from the outset for the smart world.

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.

Insurtech, also known as Digital Insurance, represents the integration of insurance services with emerging technologies. Within this domain, "digital insurers" leverage technological innovations to reshape their business and operational models, aiming to reduce costs, enhance customer experiences, and increase operational agility.

Through this instructor-led training, participants will develop a comprehensive understanding of the technologies, methodologies, and mindsets required to drive digital transformation within their organizations and across the broader industry. This course is designed for managers who seek a holistic overview, wish to cut through industry hype and jargon, and need guidance on taking initial steps toward formulating an Insurtech strategy.

Upon completing this training, participants will be equipped to:

• Discuss Insurtech and its various components with clarity and systematic insight
• Identify and demystify the role of each critical technology within the Insurtech ecosystem
• Develop a general strategy for implementing Insurtech solutions within their organization

Target Audience

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

Course Format

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

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.

This instructor-led, live training in Taiwan (onsite or remote) is aimed at engineers who wish to set up, deploy and manage a secure IoT application.

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

• Develop and deploy applications to manage IoT devices securely.
• Securely integrate IoT devices to the Cloud.
• Integrate an IoT application with existing infrastructure.

The Internet of Things (IoT) is a rapidly evolving technology domain that establishes wireless connections between physical objects and software applications for remote monitoring and control. Augmented Reality (AR) enhances user experience by seamlessly integrating virtual, computer-generated elements into the physical real-world environment, enabling businesses to deliver real-time, context-aware information. Both technologies are experiencing accelerated adoption across diverse industries.

This instructor-led live training equips participants with the foundational knowledge of IoT and AR, guiding them on how to apply these insights to their organizations' operations and strategic initiatives.

Upon completing this training, participants will be able to:

• Grasp the core principles of IoT and AR
• Gain insight into the mechanics of IoT and AR technologies
• Determine how IoT and AR technologies can be leveraged within their business strategy
• Make informed, data-driven business decisions regarding IoT and AR adoption

Target Audience

• Managers
• Entrepreneurs

Course Format

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

Note

• For inquiries regarding customized training sessions for this course, please contact us to arrange a schedule.

The Internet of Things (IoT) constitutes a network infrastructure that wirelessly connects physical objects with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. Python, a high-level programming language, is recommended for IoT development due to its clear syntax and extensive community support.

In this instructor-led live training, participants will learn how to program IoT solutions using Python.

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

• Understand the fundamentals of IoT architecture
• Learn the basics of using Raspberry Pi
• Install and configure Python on Raspberry Pi
• Learn the benefits of using Python in programming IoT systems
• Build, test, deploy, and troubleshoot an IoT system using Python and Raspberry Pi

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.

The Raspberry Pi is a compact, single-board computer.

In this instructor-led live training, participants will learn how to configure and program the Raspberry Pi to function as an interactive and robust embedded system.

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

• Configure an IDE (Integrated Development Environment) to maximize development productivity
• Program the Raspberry Pi to control devices such as motion sensors, alarms, web servers, and printers
• Understand the Raspberry Pi's architecture, including inputs and connectors for add-on devices
• Understand the various options in programming languages and operating systems
• Test, debug, and deploy the Raspberry Pi to solve real-world problems

Audience

• Developers
• Hardware/software technicians
• Technical persons in all industries
• Hobbyists

Format of the course

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

Note

• Raspberry Pi supports various operating systems and programming languages. This course will use  Linux-based Raspbian as the operating system and Python as the programming language. To request a specific setup, please contact us to arrange.
• Participants are responsible for purchasing the Raspberry Pi hardware and components.

ThingsBoard is an open-source IoT platform that provides device management, data collection, processing, and visualization capabilities 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.