Machine-to-Machine (M2M) Training Course

This training aims to clarify the nature of 5G networks and their influence on smart technologies. We will explore both the advantages and disadvantages of the relationship between 5G and IoT, while highlighting the developmental trajectory of a network designed from its inception for the smart ecosystem.

As the successor to current wireless standards, 6G is poised to revolutionize IoT ecosystems by delivering ultra-fast connectivity, advanced sensing capabilities, and seamless AI integration.

This instructor-led live training, available online or onsite, targets advanced participants eager to explore and apply the emerging synergy between 6G technologies and IoT applications.

Upon completion, learners will be able to:

• Articulate the fundamental technical principles of 6G.
• Analyze how 6G will transform IoT device communication and system architecture.
• Evaluate IoT use cases enabled by 6G across various industries.
• Develop strategies for integrating 6G capabilities into existing IoT infrastructures.

Course Format

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

Customization Options

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

Advances in technology and the exponential growth of information are reshaping business operations across various sectors, including the government. The generation of government data and the pace of digital archiving are accelerating, driven by the proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information expands and grows more complex, the management, processing, storage, security, and disposition of this data become increasingly challenging. New tools for capture, search, discovery, and analysis are enabling organizations to extract valuable insights from unstructured data. The government sector is at a critical juncture, recognizing that information is a strategic asset. Governments must now protect, leverage, and analyze both structured and unstructured information to better serve the public and fulfill mission requirements. As government leaders work to evolve their organizations into data-driven entities to successfully achieve their missions, they are establishing the foundation to correlate dependencies across events, personnel, processes, and information.

High-value government solutions will emerge from a convergence of the most disruptive technologies:

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

Big Data represents one of the intelligent industry solutions, enabling government entities to make better decisions by taking action based on patterns revealed through the analysis of large volumes of data—whether related or unrelated, structured or unstructured.

However, achieving these objectives requires far 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," Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote in a post on the OSTP Blog.

The White House took a significant step toward assisting 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 daunting as the promise it offers is encouraging. Efficient data storage is one such challenge. As budgets remain tight, agencies must minimize the per-megabyte cost of storage while keeping data easily accessible so users can retrieve it whenever and however they need it. Backing up massive amounts of data further complicates this challenge.

Effective data analysis is another major hurdle. Many agencies utilize commercial tools that allow them to sift through vast amounts of data, identifying trends that 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 fulfilling mission objectives).

Custom-developed Big Data tools are also enabling agencies to meet the need for data analysis. For example, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. The 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 connect job candidates with hiring managers.

Insurtech (also known as Digital Insurance) represents the fusion of insurance and emerging technologies. Within the Insurtech landscape, 'digital insurers' leverage technological innovations to transform their business and operational models, aiming to reduce costs, elevate customer experiences, and enhance operational agility.

This instructor-led training enables participants to comprehend the technologies, methodologies, and mindset 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, wish to cut through the hype and jargon, and take the initial steps toward establishing an Insurtech strategy.

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

• Discuss Insurtech and its various components with intelligence and systematic clarity
• Identify and demystify the role of each critical technology within the Insurtech ecosystem
• Develop a general strategy for implementing Insurtech within their organization

Target Audience

• Insurance professionals
• Technology specialists within the insurance sector
• 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 France (online or onsite) is designed for intermediate-level 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.

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

• Grasp the fundamental principles of IoT and edge computing and their significance in digital transformation.
• Recognize practical applications of IoT and edge computing in manufacturing, logistics, and energy sectors.
• Distinguish between edge and cloud computing architectures and their respective deployment scenarios.
• Deploy edge computing solutions to support predictive maintenance and real-time decision-making.

This instructor-led live training, conducted in France (online or onsite), is designed for intermediate developers, system architects, and industry professionals aiming to utilize Edge AI to enhance IoT applications with intelligent data processing and analytics.

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

• Comprehend 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 France (online or onsite) is designed for product managers and developers who aim to use Edge Computing to decentralize data management for improved 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 architectures engineered to execute specific tasks within broader operational frameworks. The Internet of Things (IoT) refers to a vast network of physical devices equipped with sensors and software, enabling them to connect, communicate, and share data via the internet.

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

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

• Comprehend the architecture and core components of embedded systems.
• Draft and compile C code to facilitate interaction with embedded hardware.
• Operate microcontroller peripherals, including timers and Analog-to-Digital Converters (ADCs).
• Grasp the role of embedded systems within IoT architectures.

Course Format

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

Customization Options

• For a tailored training experience, please contact us to arrange your specific requirements.

This instructor-led, live training in France (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 France (onsite or remote) is designed for engineers who wish to set up, deploy, and manage secure IoT applications.

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) represents an emerging technological domain that wirelessly links physical objects with software applications to enable remote sensing and control. Augmented Reality (AR) enhances user experience by integrating virtual, computer-generated elements into the physical real-world environment, allowing businesses to deliver real-time, contextual information to users. Both technologies are experiencing rapid adoption across various industries.

This instructor-led live training equips participants with the fundamental concepts of IoT and AR and demonstrates how to apply these insights to organizational operations and strategic planning.

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

• Grasp the core principles of IoT and AR
• Comprehend the operational mechanics of IoT and AR technologies
• Identify ways to leverage IoT and AR within their business strategies
• Make informed business decisions regarding IoT and AR implementation

Audience

• Managers
• Entrepreneurs

Course Format

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

Note

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

In this instructor-led, live training, participants will learn the fundamentals of IoT as they step through the creation of an Arduino-based IoT sensor system.

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

• Understand the principles of IoT, including IoT components and communication techniques.
• Learn how to use Arduino communication modules that can be used for different IoT systems.
• Learn how to use and program a mobile app to control Arduino.
• Use a Wi-Fi module to connect the Arduino to another device.
• Build and deploy their own IoT Sensor System.

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. Azure provides a comprehensive suite of cloud services, including an IoT Suite that offers preconfigured solutions to help developers accelerate their IoT project development.

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

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

• Understand the fundamentals of IoT architecture
• Install and configure Azure IoT Suite
• Learn the benefits of using Azure in programming IoT systems
• Implement various Azure IoT services (IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, IoT Device Management)
• Build, test, deploy, and troubleshoot an IoT system using Azure

Audience

• Developers
• Engineers

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.

In this instructor-led live training in France, participants will explore 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 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.

ThingsBoard is an open source IoT platform that offers 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 fundamentals of ThingsBoard features and architecture
• Build IoT applications with ThingsBoard
• Integrate ThingsBoard with Kafka for telemetry device data routing
• Integrate ThingsBoard with Apache Spark for data aggregation from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

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.