Nginx Training Course

This training aims to clarify what a 5G network is and its influence on smart technologies. We will highlight both the advantages and limitations of the relationship between 5G and IoT, while exploring the development paths of a network designed from the outset for the smart world.

6G represents the next evolution in wireless communication standards, poised to revolutionize IoT ecosystems by delivering ultra-fast connectivity, sophisticated sensing capabilities, and seamlessly integrated artificial intelligence.

This instructor-led live training, available either online or on-site, is designed for advanced professionals eager to explore and utilize the converging world of 6G technologies and IoT applications.

Upon completing this course, participants will be equipped to:

• Articulate the fundamental technical principles underlying 6G.
• Analyze how 6G will redefine IoT device communication and system architecture.
• Evaluate real-world 6G-enabled IoT use cases across various sectors.
• Develop strategies for incorporating 6G capabilities into current IoT solutions.

Course Format

• Concept-driven lectures complemented by expert-led discussions.
• Practical exercises tailored to reinforce core engineering concepts.
• Guided exploration of case studies and scenario analysis.

Customization Options

• For customized training aligned with your organization’s technology roadmap, please reach out to us to arrange.

Advancements in technology and the exponential growth of data are reshaping business operations across various sectors, including the public sector. Government data generation and digital archiving rates are accelerating due to the rapid proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information expands and becomes more complex, the management, processing, storage, security, and disposition of this data also grow more intricate. New capture, search, discovery, and analysis tools are enabling organizations to extract valuable insights from unstructured data. The government sector is reaching a tipping point, recognizing information as a strategic asset that must be protected, leveraged, and analyzed—both structured and unstructured—to better serve missions and meet requirements. As government leaders strive to evolve into data-driven organizations, they are laying the groundwork to correlate dependencies across events, people, processes, and information.

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

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

Big Data represents an intelligent industry solution that enables government entities 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 far more than simply accumulating massive quantities of data. As Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote on the OSTP Blog, "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."

In 2012, the White House took a significant step toward helping agencies identify these technologies by establishing the National Big Data Research and Development Initiative. This initiative allocated over $200 million to maximize the potential of the Big Data explosion and the tools needed to analyze it.

The challenges posed by Big Data are nearly as daunting as its promise is encouraging. Efficient data storage is one such challenge. 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 heightens this challenge.

Effective data analysis presents another major hurdle. Many agencies use commercial tools to sift through vast amounts of data, identifying trends that help them operate more efficiently. A recent study by MeriTalk revealed 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 allowing 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 find 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 session in Czech Republic (online or onsite) targets intermediate-level 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.

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

• Understand the fundamental principles of IoT and edge computing and their role in digital transformation.
• Identify relevant use cases for IoT and edge computing in manufacturing, logistics, and energy sectors.
• 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 Czech Republic (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 Czech Republic (online or on-site) is designed for product managers and developers who wish to use Edge Computing to decentralize data management for improved 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 specific tasks within larger frameworks. The Internet of Things (IoT) refers to a vast network of physical devices equipped with sensors and software, enabling them to connect, communicate, and exchange data via the internet.

This instructor-led live training, available either online or on-site, is designed for technical professionals at the beginner level who aim to grasp and implement embedded systems and IoT concepts using C programming and microcontroller architectures.

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

• Comprehend the architecture and constituent elements of embedded systems.
• Write and compile C code to facilitate interaction with embedded hardware.
• Utilize microcontroller peripherals, including timers and Analog-to-Digital Converters (ADCs).
• Recognize the role embedded systems play within IoT architectures.

Course Format

• Engaging lectures paired with discussions.
• Ample opportunities for exercises and practical application.
• Hands-on implementation within a live laboratory environment.

Customization Options

• For those seeking a customized training experience, please reach out to us to make the necessary arrangements.

This instructor-led, live training in Czech Republic (available online or onsite) is designed for intermediate-level professionals aiming to apply Federated Learning to optimize IoT and edge computing solutions.

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

• Grasp the fundamental principles and advantages of Federated Learning in IoT and edge computing contexts.
• Deploy Federated Learning models on IoT devices to facilitate decentralized AI processing.
• Minimize latency and enhance real-time decision-making capabilities in edge computing environments.
• Overcome challenges associated with data privacy and network constraints in IoT systems.

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 technologies. Azure provides a comprehensive suite of cloud services, including an IoT Suite comprised of preconfigured solutions designed to help developers accelerate the development 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:

• Grasp the fundamentals of IoT architecture
• Install and configure the Azure IoT Suite
• Understand the advantages of leveraging Azure for programming IoT systems
• Implement various Azure IoT services, including IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, and IoT Device Management
• Build, test, deploy, and troubleshoot an IoT system using Azure

Audience

• Developers
• Engineers

Course Format

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

Note

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

The goal of this training is to introduce participants to the world of the Internet of Things (smart solutions) and blockchain, while demonstrating the advantages and disadvantages of these technological domains.

The Internet of Things (IoT) represents a network infrastructure that wirelessly links physical objects with software applications, enabling seamless communication, data exchange, network connectivity, cloud computing integration, and data acquisition. C is a versatile, general-purpose programming language highly recommended for IoT development due to its widespread adoption 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 developing IoT systems in C
• Comprehend the core principles of IoT architecture
• Identify the advantages of utilizing C for IoT system programming
• Construct, test, deploy, and troubleshoot an IoT system implemented in C

Target Audience

• Software Developers
• Engineers

Course Format

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

Note

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

Unlike other technologies, IoT is far more complex, encompassing almost every branch of core engineering—mechanical, electronics, firmware, middleware, cloud, analytics, and mobile. For each of its engineering layers, there are aspects of economics, standards, regulations, and the evolving state of the art. This is the first time a modest course is offered to cover all of these critical aspects of IoT Engineering.

Summary

An advanced training program covering the current state of the art in the Internet of Things.

Cuts across multiple technology domains to develop awareness of an IoT system, its components, and how it can help businesses and organizations.

Live demo of model IoT applications to showcase practical IoT deployments across different industry domains, such as Industrial IoT, Smart Cities, Retail, Travel & Transportation, and use cases around connected devices & things.

Target Audience

Managers responsible for business and operational processes within their respective organizations who want to know how to harness IoT to make their systems and processes more efficient.

Entrepreneurs and Investors who are looking to build new ventures and want to develop a better understanding of the IoT technology landscape to see how they can leverage it effectively.

Estimates for the Internet of Things (IoT) market value are massive. By definition, IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. IoT will account for an increasingly huge number of connections: 1.9 billion devices today, and 9 billion by 2018. That year, it will be roughly equal to the number of smartphones, smart TVs, tablets, wearable computers, and PCs combined.

In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking systems, RFID, lighting and heating products, and a number of applications in the Industrial Internet.

However, the underlying technologies of IoT are nothing new, as M2M communication existed since the birth of the Internet. What changed in the last couple of years is the emergence of numerous inexpensive wireless technologies added by the overwhelming adoption of smartphones and tablets in every home. The explosive growth of mobile devices has led to the present demand for IoT.

Due to unbounded opportunities in IoT business, a large number of small and medium-sized entrepreneurs jumped on the bandwagon of the IoT gold rush. Also, due to the emergence of open-source electronics and IoT platforms, the cost of developing IoT systems and further managing their sizable production is increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their devices with the Internet or mobile apps.

This training is intended for a technology and business review of an emerging industry so that IoT enthusiasts and entrepreneurs can grasp the basics of IoT technology and business.

Course Objective

The main objective of the course is to introduce emerging technological options, platforms, and case studies of IoT implementation in home & city automation (smart homes and cities), Industrial Internet, healthcare, government, mobile cellular, and other areas.

Basic introduction of all the elements of IoT: Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data-analytics, and Total control plane.

M2M Wireless protocols for IoT: WiFi, Zigbee/Zwave, Bluetooth, ANT+ : When and where to use which one?

Mobile/Desktop/Web app for registration, data acquisition, and control – Available M2M data acquisition platforms for IoT: Xively, Omega, NovoTech, etc.

Security issues and security solutions for IoT.

Open source/commercial electronics platforms for IoT: Raspberry Pi, Arduino, ArmMbedLPC, etc.

Open source/commercial enterprise cloud platforms for AWS-IoT apps, Azure-IoT, Watson-IoT cloud, in addition to other minor IoT clouds.

Studies of the business and technology of some of the common IoT devices like Home automation, Smoke alarm, vehicles, military, home health, etc.

The Internet of Things (IoT) represents a network infrastructure that wirelessly links physical objects with software applications, enabling seamless communication and data exchange through network protocols, cloud computing, and data capture capabilities. Java, a versatile general-purpose language renowned for its "write once, run anywhere" philosophy, is highly recommended for IoT development due to its superior portability and efficiency.

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 capable of:

• Installing and configuring essential tools and frameworks, such as the Eclipse Open IoT Stack, to program IoT systems with Java
• Comprehending the core principles of IoT architecture
• Leveraging the Eclipse Open IoT Stack for Java to establish connections and manage devices within an IoT solution
• Constructing, testing, and deploying IoT systems utilizing Java

Audience

• Developers
• Engineers

Format of the course

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

Note

• For those interested in requesting customized training for this course, please contact us to make arrangements.

IoT technology differs significantly from other domains due to its complexity, spanning nearly every core engineering branch: Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each engineering layer involves economic considerations, standards, regulations, and evolving best practices. This course offers a unique opportunity to cover all critical aspects of IoT Engineering for the first time.

For manufacturing professionals, the most critical aspect is understanding advancements in the Industrial Internet of Things (IIoT), including predictive and preventative maintenance, condition-based machine monitoring, production and energy optimization, supply-chain efficiency, and uptime optimization for manufacturing utilities.

Summary

• An advanced training program covering the state-of-the-art in Internet of Things technologies within Smart Factories.
• Interdisciplinary approach to develop awareness of IoT systems, their components, and their value for manufacturing managerial professionals.
• Live demonstrations of model IIoT applications designed for smart factories.

Target Audience

• Managers responsible for business and operational processes within their manufacturing organizations who wish to leverage IoT to enhance system and process efficiency.

Duration 3 Days (8 hours per day)

Market estimates for the Internet of Things (IoT) are substantial. By definition, IoT is an integrated and dispersed layer of devices, sensors, and computing power that overlays consumer, business-to-business, and government industries. The number of connections is growing rapidly: from 1.9 billion devices currently to an estimated 9 billion by 2018. By that year, IoT connections will roughly equal the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

In the consumer sector, many products and services have already integrated with IoT, including kitchen and home appliances, parking systems, RFID, lighting, heating products, and various Industrial Internet applications.

While the underlying technologies of IoT are not new—Machine-to-Machine (M2M) communication has existed since the inception of the Internet—the landscape has shifted in recent years. This shift is driven by the emergence of inexpensive wireless technologies and the widespread adoption of smartphones and tablets in households. The explosive growth of mobile devices has fueled the current demand for IoT.

Industrial IoT (IIoT) has been widely adopted in manufacturing since 2014, leading to numerous innovations. This course introduces all important aspects of these innovations in the IIoT domain.

This training is designed for a technology and business review of this emerging industry, enabling IoT enthusiasts and entrepreneurs to grasp the fundamentals of IoT technology and business models.

Course Objective

The primary objective is to introduce emerging technological options, platforms, and case studies of IoT implementation in smart factories for the manufacturing sector.

1. Study of business and technology of common IIoT platforms such as Siemens MindSphere and Azure IoT.
2. Open-source and commercial enterprise cloud platforms for AWS IoT apps, Azure IoT, Watson IoT, Mindsphere IIoT cloud, and other minor IoT cloud services.
3. Open-source and commercial electronics platforms for IoT, including Raspberry Pi, Arduino, and Arm Mbed LPC.
4. Security issues and solutions for IIoT.
5. Mobile/Desktop/Web applications for registration, data acquisition, and control.
6. M2M wireless protocols for IoT—WiFi, LoRa, BLE, Ethernet, EtherCAT, PLC—and guidance on when and where to use each.
7. Basic introduction to all IoT elements: Mechanical, Electronics/Sensor platform, Wireless and wired protocols, Mobile-to-Electronics integration, Mobile-to-Enterprise integration, Data Analytics, and the total control plane.

In this instructor-led live training in Czech Republic, participants will explore the various aspects of NB-IoT (also known as LTE Cat NB1) while developing and deploying 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 they integrate to form an ecosystem.
• Understand and explain the security features built into NB-IoT devices.
• Develop a simple application to track NB-IoT devices.