Introduction to IoT Using Raspberry Pi Training Course

The aim of the training is to explain what the 5G network is and what impact it has on smart technologies. I want to show you both the advantages and disadvantages of these technological relationships (5G / IoT) and show you the directions of development of the network, which - from the very beginning - was dedicated to the smart world.

6G is the next-generation wireless communication standard set to revolutionize IoT ecosystems by offering ultra-fast connectivity, advanced sensing capabilities, and seamless integration with AI.

This instructor-led, live training (available online or on-site) is designed for advanced-level participants who want to understand and leverage the emerging synergy between 6G technologies and IoT applications.

By completing this course, learners will be able to:

• Explain the fundamental technical concepts behind 6G.
• Evaluate how 6G will transform communication and architecture in IoT devices.
• Analyze real-world use cases of 6G-enabled IoT across various industries.
• Develop strategies for integrating 6G capabilities into existing IoT solutions.

Format of the Course

• Lectures focused on core concepts, complemented by expert discussions.
• Practical exercises designed to reinforce key engineering principles.
• Case studies and scenario analyses conducted in a guided learning environment.

Course Customization Options

• For customized versions of this training that align with your organization's technology roadmap, please contact us to arrange.

Technological advancements and the exponential growth of information are reshaping business practices across various sectors, including government. The surge in mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals is driving a significant increase in data generation and digital archiving within government entities. As the volume and complexity of digital information expand, the challenges related to managing, processing, storing, securing, and disposing of this data become more intricate. However, new tools for capturing, searching, discovering, and analyzing unstructured data are enabling organizations to derive valuable insights. The government sector is at a critical juncture, recognizing that information is a strategic asset. To better serve the public and meet mission requirements, government agencies need to protect, leverage, and analyze both structured and unstructured information. As leaders strive to transform their organizations into data-driven entities, they are establishing frameworks to identify and correlate dependencies across events, people, processes, and information.

High-impact government solutions will emerge from the integration of the most transformative technologies:

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

Big Data is a key intelligent industry solution that enables government agencies to make informed decisions by analyzing large volumes of data—both structured and unstructured. By identifying patterns within these vast datasets, governments can take more effective actions.

However, achieving these outcomes requires more than just collecting massive amounts of data. "Interpreting such vast quantities of Big Data necessitates cutting-edge tools and technologies capable of analyzing and extracting meaningful insights from diverse streams of information," Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote in a blog post.

In 2012, the White House took a significant step toward helping agencies find these necessary tools by launching the National Big Data Research and Development Initiative. This initiative allocated over $200 million to capitalize on the surge in Big Data and develop the required analytical tools.

The challenges posed by Big Data are as formidable as its potential is promising. Efficient data storage is a major challenge, especially given budget constraints. Agencies must reduce the cost per megabyte of storage while ensuring easy access for users when and how they need it. Backing up large volumes of data further complicates this task.

Effective data analysis presents another significant challenge. Many agencies use commercial tools to sift through vast datasets, identifying trends that can enhance operational efficiency. A recent study by MeriTalk found that federal IT executives believe Big Data could help agencies save more than $500 billion while also achieving their mission objectives.

Custom-developed Big Data tools are also aiding agencies in analyzing their data. 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 a critical link that can alert doctors to potential aortic aneurysms before they occur. It is also used for more routine tasks, such as filtering through resumes to match job candidates with hiring managers.

Insurtech, or Digital Insurance, represents the integration of insurance with cutting-edge technologies. In this domain, "digital insurers" leverage technological innovations to streamline their business and operational models, aiming to cut costs, enhance customer experiences, and boost operational agility.

This instructor-led training equips participants with a comprehensive understanding of the technologies, methodologies, and mindset required for digital transformation within their organizations and across the industry. The training is designed for managers who need an overarching view to separate fact from hype, demystify jargon, and take initial steps in formulating an Insurtech strategy.

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

• Engage in intelligent and systematic discussions about Insurtech and its various components.
• Clearly identify and understand the role of each key technology within Insurtech.
• Develop a general strategy for implementing Insurtech within their organization.

Audience

• Insurance companies
• Technologists in the insurance sector
• Insurance stakeholders
• Consultants and business analysts

Format of the course

• A combination of lectures, discussions, exercises, and group activities centered around case studies.

This instructor-led, live training in Taiwan (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 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:

• 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 Taiwan (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.

Embedded systems are specialized computing systems designed to perform specific functions within larger systems. IoT (Internet of Things) refers to a network of interconnected physical devices equipped with sensors and software that communicate and exchange data over the internet.

This instructor-led, live training (available online or on-site) is targeted at beginner-level technical professionals who wish to understand and apply embedded systems and IoT concepts using C programming and microcontroller architectures.

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

• Grasp the architecture and components of embedded systems.
• Write and compile C code for interacting with embedded hardware.
• Work with microcontroller peripherals such as timers and ADCs (Analog-to-Digital Converters).
• Understand how embedded systems integrate into IoT architectures.

Format of the Course

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

Course 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) 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.

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 an innovative technology domain that enables the wireless connection of physical objects and software applications for remote sensing and control. Augmented Reality (AR) enhances user experiences by integrating virtual, computer-generated elements with the real-world environment, providing businesses with a means to offer users real-time, enriched information about their surroundings. These two technologies are witnessing rapid adoption across various industries.

In this instructor-led, live training session, participants will gain an understanding of the fundamentals of IoT and AR and explore how these technologies can be applied to enhance their organizations' operations and strategies.

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

• Grasp the core principles of IoT and AR
• Learn how IoT and AR technologies function
• Understand how IoT and AR can be leveraged for their business strategies
• Make well-informed business decisions regarding IoT and AR

Audience

• Managers
• Entrepreneurs

Format of the Course

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

Note

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

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

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:

• Grasp the fundamentals of IoT architecture
• Master the basics of using Raspberry Pi
• Install and configure Python on a Raspberry Pi
• Understand the advantages of using Python for programming IoT systems
• Build, test, deploy, and troubleshoot an IoT system with Python and Raspberry Pi

Audience

• Developers
• Engineers

Format of the course

• Combination of lecture, discussion, exercises, and extensive 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.

Raspberry Pi is a compact, single-board computer.

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

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

• Configure an IDE (integrated development environment) for optimal development efficiency
• Program the Raspberry Pi to control devices such as motion sensors, alarms, web servers, and printers.
• Understand the architecture of the Raspberry Pi, including its input and connector options for add-on devices.
• Explore the various programming languages and operating systems available
• Test, debug, and deploy the Raspberry Pi to address real-world challenges

Audience

• Developers
• Hardware/software technicians
• Technical professionals from all industries
• Hobbyists

Format of the course

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

Note

• Raspberry Pi supports a variety of operating systems and programming languages. This course will use Linux-based Raspbian as the operating system and Python as the programming language. For any specific setup requests, 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 for your IoT solutions.

In this instructor-led, live training, participants will learn how to integrate ThingsBoard into their IoT projects.

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

• Install and configure ThingsBoard
• Understand the core features and architecture of ThingsBoard
• Build IoT applications using ThingsBoard
• Integrate ThingsBoard with Kafka for telemetry data routing
• Integrate ThingsBoard with Apache Spark for aggregating data from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

Format of the course

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

Note

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