IoT Programming with Python 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 represents the next generation of wireless communication standards, poised to revolutionize IoT ecosystems through ultra-fast connectivity, advanced sensing, and integrated AI capabilities.

This instructor-led, live training (available both online and onsite) is designed for advanced-level participants who aim to understand and leverage the emerging intersection of 6G technologies and IoT applications.

Upon 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 various 6G-enabled IoT use cases across different industries.
• Develop strategies for integrating 6G capabilities into existing IoT solutions.

Format of the Course

• Concept-focused lectures complemented by expert-led 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 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.

Technological advancements and the exponential growth of information are reshaping business operations across various sectors, including government. The proliferation of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals has significantly increased the volume of data generated and digitally archived by government entities. As digital information becomes more extensive and complex, managing, processing, storing, securing, and disposing of this data also grows in complexity. Innovative 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. To better serve and meet mission requirements, government bodies need to protect, leverage, and analyze both structured and unstructured information effectively. Government leaders are working to transform their organizations into data-driven entities by establishing the necessary infrastructure to correlate dependencies among events, people, processes, and information.

High-value solutions in the government sector will emerge from a combination of the most disruptive 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 agencies to make better decisions by leveraging patterns identified through the analysis of large, diverse data sets—both structured and unstructured.

Achieving these goals involves more than just collecting vast amounts of data. "To make sense of these volumes of Big Data, advanced tools and technologies are needed to analyze and extract meaningful insights from extensive and varied information streams," wrote Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy in a blog post.

To assist agencies in finding these necessary technologies, the White House launched the National Big Data Research and Development Initiative in 2012. The initiative allocated more than $200 million to capitalize on the surge of Big Data and the tools required for its analysis.

While the potential of Big Data is promising, it also presents significant challenges. Efficient data storage is one such challenge. Budget constraints mean agencies must minimize storage costs per megabyte while ensuring easy access to data when needed. Backing up large volumes of data adds to this complexity.

Effective data analysis is another major hurdle. Many agencies use commercial tools to sift through vast amounts of data, identifying trends that can enhance operational efficiency. A recent study by MeriTalk found that federal IT executives believe Big Data could help agencies save over $500 billion while also achieving their mission objectives.

Custom-developed Big Data solutions 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 government entities. This system has helped medical researchers identify early warning signs for aortic aneurysms and is used for routine tasks such as matching job candidates with hiring managers.

Insurtech, also known as Digital Insurance, represents the integration of insurance with modern technologies. In this domain, "digital insurers" leverage technological advancements to streamline their business and operational models, thereby reducing costs, enhancing customer experiences, and increasing operational agility.

This instructor-led training aims to provide participants with a deep understanding of the technologies, methods, and mindset required to drive digital transformation within their organizations and across the industry. The course is specifically targeted at managers who need to grasp the broader picture, demystify the hype and technical jargon, and take initial steps in formulating an Insurtech strategy.

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

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

Audience

• Insurance companies
• Technologists in the insurance sector
• Stakeholders in the insurance industry
• 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 Serbia (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 Serbia (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 Serbia (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.

This instructor-led, live training in Serbia (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) is a network infrastructure that connects physical objects and software applications wirelessly, enabling them to communicate with each other and exchange data through network communications, cloud computing, and data capture.

In this instructor-led, live training, participants will gain an understanding of the fundamentals of IoT as they work through the process of creating an IoT sensor system using the Raspberry Pi.

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

• Comprehend the principles of IoT, including its components and communication techniques
• Learn how to configure the Raspberry Pi for IoT applications
• Develop and deploy their own IoT Sensor System

Audience

• Hobbyists
• Hardware and software engineers and technicians
• Technical professionals from all industries
• Beginner developers

Format of the course

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

Note

• The 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. For a specific setup, please contact us to arrange.
• Participants are responsible for purchasing the necessary Raspberry Pi hardware and components.

In this instructor-led, live training in Serbia, 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:

• Set up an integrated development environment (IDE) for optimal development productivity
• 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 inputs and connectors for add-on devices.
• Explore the various options in programming languages and operating systems
• 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 mix of lectures, discussions, exercises, and extensive hands-on practice

Note

• Raspberry Pi supports multiple 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 for your IoT solution.

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 core features and architecture of ThingsBoard
• Build IoT applications using ThingsBoard
• Integrate ThingsBoard with Kafka for device 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.