Nginx Training Course

The objective of this training is to clarify the nature of 5G networks and their influence on smart technologies. The course aims to present both the advantages and disadvantages of the relationship between these technologies (5G and IoT), while highlighting the developmental directions of a network designed from the outset for the smart world.

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.

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.

Embedded systems are specialized computing solutions engineered to execute specific tasks within broader systems. The Internet of Things (IoT) refers to a network of physical devices equipped with sensors and software, enabling them to communicate and share data via the internet.

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

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

• Grasp the architecture and key components 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).
• Comprehend the role of embedded systems within IoT architectures.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical sessions.
• Hands-on implementation within a live laboratory environment.

Options for Course Customization

• For inquiries regarding customized training for this course, please reach out to us to make arrangements.

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.

The Internet of Things (IoT) represents a network infrastructure that wirelessly connects physical devices with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture mechanisms. Azure provides a robust suite of cloud services that includes an IoT Suite with preconfigured solutions designed to help developers accelerate the creation of IoT projects.

In this instructor-led live training, participants will gain the skills needed to develop IoT applications using Azure.

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

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

Audience

• Developers
• Engineers

Format of the course

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

Note

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

The objective of this training is to provide an introduction to the realms of the Internet of Things (smart solutions) and blockchain technology, highlighting the benefits and drawbacks associated with these technological domains.

The Internet of Things (IoT) refers to a network infrastructure that wirelessly connects physical devices with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. C is a general-purpose programming language recommended for IoT development due to its widespread use and benefits in low-level programming.

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

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

• Install and configure NetBeans for programming IoT systems with C
• Grasp the fundamentals of IoT architecture
• Understand the advantages of using C for IoT programming
• Build, test, deploy, and troubleshoot an IoT system using C

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 arrange it.

Unlike other technologies, the Internet of Things (IoT) is significantly more complex, spanning nearly every branch of core engineering including Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each engineering layer involves aspects of economics, standards, regulations, and the evolving state of the art. For the first time, a modest course is offered to cover all 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 in an effective manner.

Estimates for the Internet of Things (IoT) market value are massive, since 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. The 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, 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 has 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 led to the present demand for IoT.

Due to unbounded opportunities in the 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 an IoT system and further managing its 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/entrepreneurs can grasp the basics of IoT technology and business.

Course Objective

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, and 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 common IoT devices like Home automation, Smoke alarms, vehicles, military, home health, etc.

The Internet of Things (IoT) represents a network infrastructure that wirelessly connects physical objects with software applications, enabling seamless communication, data exchange, and integration through network communications, cloud computing, and data capture mechanisms. Java, renowned for its "write once, run anywhere" capability, is a versatile language recommended for IoT development due to its high portability and efficiency.

This instructor-led live training will guide participants in developing IoT solutions using Java.

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

• Install and configure necessary tools and frameworks, such as the Eclipse Open IoT Stack, for Java-based IoT programming
• Comprehend the core principles of IoT architecture
• Utilize the Eclipse Open IoT Stack for Java to connect and manage devices within an IoT environment
• Construct, test, and deploy IoT systems using Java

Target Audience

• Software Developers
• Engineers

Course Format

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

Note

• For customized training options, please reach out to us to arrange a tailored session.

In contrast to other technologies, IoT is significantly more complex, spanning nearly every core engineering discipline: Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each engineering layer involves considerations of economics, standards, regulations, and the evolving state of the art. For the first time, this modest course covers all these critical aspects of IoT Engineering.

For manufacturing professionals, the most critical aspect is understanding advancements in the Industrial Internet of Things. This includes predictive and preventative maintenance, condition-based monitoring of machines, production and energy optimization, supply-chain optimization, and uptime of manufacturing utilities, among other factors.

Summary

• An advanced training program covering the current state of the art in the Internet of Things within Smart Factories.
• Cross-referencing multiple technology domains to develop awareness of IoT systems, their components, and how they can benefit manufacturing managerial professionals.
• Live demonstration of model IIoT applications for smart factories.

Target Audience

• Managers responsible for business and operational processes within their respective manufacturing organizations who wish to learn how to leverage IoT to enhance the efficiency of their systems and processes.

Duration 3 Days (8 hours per day)

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. The number of IoT connections is increasing rapidly: from 1.9 billion devices today to an estimated 9 billion by 2018. In that year, the number of connected devices will roughly equal the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

In the consumer space, many products and services have already transitioned into the IoT ecosystem, including kitchen and home appliances, parking systems, RFID, lighting, heating products, and various applications within the Industrial Internet.

While the underlying technologies of IoT are not new—Machine-to-Machine (M2M) communication has existed since the birth of the Internet—what has changed in recent years is the emergence of numerous inexpensive wireless technologies. This change is driven by the widespread adoption of smartphones and tablets in every home. The explosive growth of mobile devices has led to the current demand for IoT solutions.

Industrial IoT (IIoT) for manufacturing has been in wide use since 2014, with a large number of IIoT innovations occurring since then. This course will introduce all the important aspects of these innovations in the IIoT field.

This training is intended as a technology and business review of this emerging industry, allowing IoT enthusiasts and entrepreneurs to grasp the basics of IoT technology and business models.

Course Objective

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

1. Studies of the business and technology of common IIoT platforms like Siemens MindSphere and Azure IoT.
2. Open-source and commercial enterprise cloud platforms for AWS IoT, Azure IoT, Watson IoT, MindSphere IIoT cloud, in addition to other minor IoT clouds.
3. Open-source and commercial electronics platforms for IoT: Raspberry Pi, Arduino, ARM MbedLPC, etc.
4. Security issues and security solutions for IIoT.
5. Mobile/Desktop/Web apps for registration, data acquisition, and control.
6. M2M Wireless protocols for IoT: WiFi, LoRa, BLE, Ethernet, EtherCAT, PLC: When and where to use each?
7. Basic introduction to all IoT elements: Mechanical, Electronics/Sensor platform, Wireless and wireline protocols, Mobile-to-Electronics integration, Mobile-to-enterprise integration, Data analytics, and the Total control plane.

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.