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.

Positioned as the next generation of wireless standards, 6G is set to revolutionize IoT ecosystems by delivering ultra-fast connectivity, advanced sensing capabilities, and integrated AI.

This instructor-led live training, available online or onsite, targets advanced-level professionals seeking to understand and harness the emerging convergence of 6G technologies and IoT applications.

Upon completion, learners will be equipped to:

• Articulate the fundamental technical concepts underlying 6G.
• Assess how 6G will transform IoT device communication and architectural design.
• Evaluate IoT use cases enabled by 6G across various industries.
• Develop strategies for integrating 6G capabilities into current IoT solutions.

Course Format

• Concept-driven lectures combined with expert-led discussions.
• Practical exercises designed to reinforce core engineering principles.
• Guided case studies and scenario analysis.

Customization Options

• For customized 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 numerous sectors, including government. Government data creation and digital archiving are accelerating, driven by the proliferation of mobile devices and apps, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information becomes more voluminous and complex, the management, processing, storage, security, and retention of this data become increasingly challenging. New tools for capture, search, discovery, and analysis are enabling organizations to derive valuable insights from unstructured data. The government sector is at a critical juncture, recognizing information as a strategic asset. Governments must protect, leverage, and analyze both structured and unstructured information to better serve citizens and meet mission requirements. As government leaders strive to evolve into data-driven organizations, they are establishing the foundation to correlate dependencies across events, personnel, processes, and information.

High-impact government solutions are emerging from the integration of disruptive technologies:

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

Big Data serves as an intelligent industry solution, enabling governments 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 more than just accumulating vast 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," wrote 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 a significant step toward helping agencies identify these technologies by establishing the National Big Data Research and Development Initiative in 2012. This initiative included over $200 million to capitalize on 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 cost per megabyte of storage and ensure data is easily accessible, allowing users to retrieve it when and how they need it. Backing up massive quantities of data further compounds this challenge.

Effective data analysis is another major hurdle. Many agencies utilize commercial tools to sift through vast amounts of data, identifying trends that improve operational efficiency. (A recent MeriTalk study found 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 enabling agencies to meet their analysis needs. For example, 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 can alert doctors to aortic aneurysms before they occur. It is also used for routine tasks, such as screening resumes to connect job candidates with hiring managers.

Insurtech (also known as Digital Insurance) represents the intersection of the insurance industry and emerging technologies. Within the Insurtech sector, 'digital insurers' leverage technological innovations to refine their business and operational models, aiming to lower costs, elevate the customer experience, and increase operational agility.

This instructor-led training helps participants understand the technologies, methods, and mindset required to drive digital transformation within their organizations and across the broader industry. The course is designed for managers who need to gain a comprehensive overview, cut through hype and jargon, and take initial steps in developing an Insurtech strategy.

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

• Discuss Insurtech and its various components intelligently and systematically
• Identify and clarify the role of key technologies within Insurtech.
• Develop a general strategy for implementing Insurtech within their organization

Audience

• Insurance companies
• Technologists working in the insurance industry
• Stakeholders in the insurance sector
• Consultants and business analysts

Course Format

• A blend of lectures, discussions, exercises, and case study group activities

This instructor-led, live training in Serbia (online or onsite) is targeted at intermediate-level IT professionals and business managers who wish to understand the potential of IoT and edge computing for enhancing efficiency, real-time processing, and innovation across various industries.

Upon completion 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) targets intermediate-level developers, system architects, and industry professionals eager to leverage Edge AI to boost IoT applications with intelligent data processing and analytics.

By the conclusion 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 designed for product managers and developers aiming to decentralize data management via Edge Computing to achieve faster performance, utilizing smart devices located within the source network.

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

• Understand the core concepts and advantages of Edge Computing.
• Identify use cases and examples where Edge Computing can be effectively applied.
• Design and build Edge Computing solutions for faster data processing and reduced operational costs.

Establish a solid foundation in designing and managing resilient edge computing infrastructure. Gain insights into open hybrid cloud setups, workload management across various clouds, and strategies for ensuring flexibility and redundancy. This training equips learners with the essential knowledge needed to build scalable, secure infrastructure capable of supporting the dynamic demands of modern applications through edge computing.

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

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

• Comprehend the principles and advantages of Federated Learning in IoT and edge computing.
• Deploy Federated Learning models on IoT devices for decentralized AI processing.
• Minimize latency and enhance real-time decision-making capabilities in edge computing environments.
• Overcome challenges related to data privacy and network limitations in IoT systems.

The Internet of Things (IoT) constitutes a network infrastructure that wirelessly links physical objects with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture.

In this instructor-led live training, participants will grasp the fundamentals of IoT by guiding them through the creation of an IoT sensor system using the Raspberry Pi.

Upon completion of this training, participants will be capable of:

• Understanding IoT principles, including its components and communication techniques
• Learning how to configure the Raspberry Pi specifically for IoT applications
• Building and deploying their own IoT Sensor System

Audience

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

Format of the course

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

Note

• Raspberry Pi supports a variety of operating systems and programming languages. This course utilizes 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.

In this instructor-led live training in Serbia, 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 understand how they integrate to form an ecosystem.
• Understand and explain the security features inherent in NB-IoT devices.
• Develop a simple application to track NB-IoT devices.

The Raspberry Pi is a compact, single-board computer.

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

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

• Configure an Integrated Development Environment (IDE) to maximize development productivity.
• Program the Raspberry Pi to control devices such as motion sensors, alarms, web servers, and printers.
• Grasp the architecture of the Raspberry Pi, including its inputs and connectors for add-on devices.
• Understand the various options available in programming languages and operating systems.
• Test, debug, and deploy the Raspberry Pi to address real-world problems.

Audience

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

Format of the course

• A mix of lectures, discussions, exercises, and intensive hands-on practice.

Note

• The Raspberry Pi supports a wide range of operating systems and programming languages. This course will utilize 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 Raspberry Pi hardware and components themselves.

ThingsBoard is an open-source IoT platform providing device management, data collection, processing, and visualization for your IoT solutions.

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

Upon completing this training, participants will be able to:

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

Target Audience

• Software engineers
• Hardware engineers
• Developers

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.