IoT Programming with Python Training Course

This training aims to clarify what the 5G network is and its impact on smart technologies. We will examine both the advantages and disadvantages of the relationship between these technologies (5G / IoT) and explore the developmental directions of a network that has been dedicated to the smart world from its inception.

6G represents the subsequent generation of wireless communication standards, poised to revolutionize IoT ecosystems through ultra-high-speed connectivity, sophisticated sensing capabilities, and seamlessly integrated AI functions.

This instructor-led live training, available both online and onsite, is designed for advanced-level participants seeking to comprehend and capitalize on the emerging convergence of 6G technologies and IoT applications.

Upon completion of this course, learners will be equipped to:

• Articulate the fundamental technical principles underpinning 6G.
• Analyze how 6G will transform IoT device communication and structural frameworks.
• Evaluate 6G-enabled IoT use cases across various sectors.
• Develop strategies for incorporating 6G capabilities into current IoT solutions.

Course Format

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

Course Customization Options

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

Technological advancements and the exponential growth of information are reshaping business operations across numerous sectors, including government. The generation of government data and the pace of digital archiving are accelerating, driven by the surge in mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information becomes more expansive and complex, managing, processing, storing, securing, and disposing of this data grows increasingly difficult. New tools for capturing, searching, discovering, and analyzing data are enabling organizations to extract valuable insights from their unstructured data. The government sector is reaching a critical juncture, recognizing information as a strategic asset. Government bodies must protect, leverage, and analyze both structured and unstructured information to better serve the public and fulfill mission requirements. As government leaders work to transform into data-driven organizations to successfully achieve their missions, they are establishing the framework to correlate dependencies across events, people, processes, and information.

High-value government solutions 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 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—whether related or unrelated, structured or unstructured.

However, achieving this requires more than simply accumulating massive quantities 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 moved to assist agencies in finding these technologies by establishing 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 tools required to analyze it.

The challenges posed by Big Data are nearly as formidable as its promise is encouraging. Efficiently storing data is one such challenge. Budgets are always tight, so agencies must minimize the cost per megabyte of storage while keeping data readily accessible so users can retrieve it when and how they need it. Backing up massive amounts of data further intensifies this challenge.

Effectively analyzing the data is another major hurdle. Many agencies utilize commercial tools that allow them 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 more than $500 billion while also meeting mission objectives.)

Custom-developed Big Data tools are also enabling agencies to address their data analysis 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 can alert doctors to aortic aneurysms before they occur. It is also used for more routine tasks, such as sifting through resumes to match job candidates with hiring managers.

Insurtech (also known as Digital Insurance) represents the convergence of the insurance industry with new technologies. Within the Insurtech sector, "digital insurers" leverage technological innovations to transform their business and operating models, aiming to reduce costs, improve customer experiences, and increase operational agility.

This instructor-led training will help participants understand the technologies, methods, and mindsets required to drive digital transformation within their organizations and across the broader industry. The course is specifically designed for managers who need a comprehensive overview, want to cut through the hype and jargon, and are ready to take initial steps toward establishing an Insurtech strategy.

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

• Discuss Insurtech and its various components intelligently and systematically
• Identify and demystify the role of each key technology within Insurtech.
• Draft a general strategy for implementing Insurtech within their organization

Audience

• Insurance professionals
• Technologists working within the insurance industry
• Insurance stakeholders
• Consultants and business analysts

Course Format

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

This instructor-led, live training in Norway (online or onsite) targets intermediate-level IT professionals and business managers who want to understand how IoT and edge computing can foster efficiency, real-time processing, and innovation across different industries.

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

• Understand the core principles of IoT and edge computing and their part in digital transformation.
• Identify practical applications for IoT and edge computing in manufacturing, logistics, and energy.
• Differentiate between edge and cloud computing architectures and deployment contexts.
• Implement edge computing solutions to facilitate predictive maintenance and real-time decision-making.

This instructor-led, live training in Norway (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 Norway (online or onsite) is designed for product managers and developers seeking to decentralize data management for improved performance, by leveraging smart devices located on the source network.

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

• Grasp the fundamental concepts and benefits of Edge Computing.
• Recognize practical use cases and real-world examples of Edge Computing applications.
• Design and implement Edge Computing solutions to accelerate data processing and lower operational costs.

Embedded systems are specialized computing devices 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 and share data across the internet.

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

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

• Gaining insight into the architecture and components of embedded systems.
• Writing and compiling C code to facilitate hardware interaction.
• Utilizing microcontroller peripherals, including timers and ADCs.
• Comprehending the role of embedded systems within IoT architectures.

Course Format

• Engaging lectures and discussions.
• Extensive exercises and practical sessions.
• Practical implementation within a live-lab environment.

Options for Customizing the Course

• To arrange a tailored training session for this course, please get in touch with us.

This instructor-led, live training in Norway (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 Norway (onsite or remote) is targeted 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.

The Internet of Things (IoT) is an emerging technology domain that connects physical objects and software applications wirelessly for remote sensing and control. Augmented Reality (AR) is a technology that improves user experience by blending virtual computer-generated elements with the physical real-world environment. AR allows businesses to provide users with a real-time and real-world view of information. These are two technologies that have been seeing a rapidly growing adoption rate across multiple industries.

In this instructor-led, live training, participants will learn the fundamentals of IoT and AR and apply these learnings to their organizations' operations and strategies.

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

• Understand the fundamentals of IoT and AR
• Learn how IoT and AR technologies work
• Understand how IoT and AR technologies can be applied to their business' strategy
• Make informed business decisions about IoT and AR

Audience

• Managers
• Entrepreneurs

Format of the course

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

Note

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

The Internet of Things (IoT) refers to a network infrastructure that wirelessly links physical devices 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 master the fundamentals of IoT by building an IoT sensor system using the Raspberry Pi.

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

• Grasp the principles of IoT, including its components and communication methods
• Configure the Raspberry Pi specifically for IoT applications
• Construct and deploy their own IoT Sensor System

Audience

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

Format of the course

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

Note

• The Raspberry Pi supports various operating systems and programming languages. This course utilizes the Linux-based Raspbian operating system and Python as the programming language. For specific setup requirements, please contact us to arrange.
• Participants must purchase their own Raspberry Pi hardware and components.

In this instructor-led, live training in Norway, participants will explore 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 understand how they 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.

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

In this guided live training, participants will learn how to configure and code the Raspberry Pi to function as an interactive and robust embedded system.

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

• Configure an IDE (integrated development environment) to optimize development productivity
• Code the Raspberry Pi to manage devices such as motion sensors, alarms, web servers, and printers.
• Comprehend the Raspberry Pi's architecture, including input methods and connectors for expansion devices.
• Evaluate various programming languages and operating system options.
• Test, debug, and deploy the Raspberry Pi to address real-world challenges.

Audience

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

Course Format

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

Note

• The Raspberry Pi is compatible with multiple operating systems and programming languages. This course utilizes the Linux-based Raspbian operating system and Python as the programming language. For specific setup requirements, please contact us to make arrangements.
• Participants are responsible for acquiring the necessary Raspberry Pi hardware and components.

ThingsBoard is an open-source IoT platform that provides 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 ecosystems.

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

• Install and configure ThingsBoard
• Understand the core principles of ThingsBoard's features and architecture
• Develop IoT applications using ThingsBoard
• Integrate ThingsBoard with Kafka to route telemetry data from devices
• Integrate ThingsBoard with Apache Spark to aggregate data from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

Course format

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

Note

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