IoT (Internet of Things) - Technology Overview 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 upcoming wireless communication standard that is set to revolutionize IoT ecosystems through ultra-fast connectivity, advanced sensing, and integrated AI capabilities.

This instructor-led, live training (available online or on-site) is designed for advanced-level participants who want to understand and leverage the emerging convergence of 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 IoT device communication and architecture.
• Assess 6G-enabled IoT use cases across various industries.
• Develop strategies for integrating 6G capabilities into existing IoT solutions.

Format of the Course

• Concept-focused lectures combined with expert-led discussions.
• Applied exercises designed to reinforce key engineering principles.
• Case-based exploration and scenario analysis in a guided learning environment.

Course Customization Options

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

Delve deeper into the innovative realm of edge computing with this advanced course. Explore sophisticated architectures and tackle integration challenges, preparing to leverage the full potential of edge computing in a variety of business environments. Gain expertise in cutting-edge tools and methodologies to deploy, manage, and optimize edge computing solutions that meet specific industry needs.

Advances in technology and the exponential growth of information are reshaping how businesses operate across various sectors, including government. The rise in data generation and digital archiving within government is driven by the proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As the volume and complexity of digital information grow, the challenges of managing, processing, storing, securing, and disposing of this data also become more intricate. New tools for capturing, searching, discovering, and analyzing unstructured data are enabling organizations to derive valuable insights. The government sector is reaching a critical juncture where it recognizes that information is a strategic asset. Consequently, there is an urgent need to protect, leverage, and analyze both structured and unstructured data to better serve the public and meet mission objectives. Government leaders are working towards building data-driven organizations by establishing connections across events, people, processes, and information.

High-value government solutions will emerge from a combination of the most transformative technologies:

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

Big Data is one of the intelligent industry solutions that enable government to make informed decisions by analyzing large volumes of diverse data, both structured and unstructured. This analysis reveals patterns that can inform better decision-making.

Achieving these goals requires more than just collecting vast amounts of data. "Making sense of these massive volumes of Big Data necessitates advanced tools and technologies capable of extracting valuable insights from a wide array of information," noted Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy in a blog post.

To help agencies access these technologies, the White House launched the National Big Data Research and Development Initiative in 2012. This initiative allocated over $200 million to capitalize on the growth of Big Data and develop the necessary analytical tools.

The challenges posed by Big Data are as significant as its potential benefits. Efficient data storage is a primary concern. Budget constraints mean that agencies must keep storage costs low while ensuring easy access to data for users. Backing up large volumes of data further complicates this challenge.

Effective data analysis is another major hurdle. Many agencies use 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 also meeting 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 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, also known as Digital Insurance, represents the integration of insurance with modern technologies. In this field, "digital insurers" leverage technological advancements to optimize their business and operational models, aiming to reduce costs, enhance customer experience, and increase operational agility.

This instructor-led training equips participants with an understanding of the technologies, methods, and mindset necessary for driving digital transformation within their organizations and the broader industry. The training is designed for managers who need a comprehensive overview, to demystify hype and jargon, and to take the 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.
• Clarify and explain the role of each key technology within Insurtech.
• Develop a general strategy for implementing Insurtech within their organization.

Audience

• Insurers
• Technologists in the insurance industry
• Insurance stakeholders
• Consultants and business analysts

Format of the course

• A combination of lectures, discussions, exercises, and group activities focused on case studies.

This instructor-led, live training in Uzbekistan (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.

Combine the transformative power of AI with the agility of edge computing in this comprehensive course. Learn to deploy AI models directly on edge devices, from understanding CNN architectures to mastering knowledge distillation and federated learning. This hands-on training will equip you with the skills to optimize AI performance for real-time processing and decision-making at the edge.

This instructor-led, live training in Uzbekistan (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 Uzbekistan (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.

Build a strong foundation in designing and managing a resilient edge computing infrastructure. Learn about open hybrid cloud infrastructures, managing workloads across diverse clouds, and ensuring flexibility and redundancy. This training provides essential knowledge on creating a scalable and secure infrastructure that supports the dynamic needs of modern applications with edge computing.

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

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

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

• Understand 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 analog-to-digital converters (ADCs).
• Understand how embedded systems integrate into IoT architectures.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practical activities.
• Hands-on 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 Uzbekistan (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 Uzbekistan (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.

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

ThingsBoard is an open-source IoT platform that provides comprehensive 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 projects.

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

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

Audience

• Software engineers
• Hardware engineers
• Developers

Format of the course

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

Note

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