Internet of Things (IoT) Training in Turin

This instructor-led, live training in Turin (online or onsite) is aimed at advanced-level IoT developers and smart home enthusiasts who wish to automate IoT processes and create innovative solutions using n8n.

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

• Set up and configure n8n for IoT workflow automation.
• Integrate IoT devices and platforms using n8n nodes and connectors.
• Implement custom workflows to automate IoT tasks and processes.
• Use IoT protocols like MQTT and REST APIs within n8n workflows.
• Monitor, troubleshoot, and optimize IoT automation workflows.

Positioned to revolutionize IoT ecosystems through ultra-fast connectivity, advanced sensing, and integrated AI capabilities, 6G represents the next-generation wireless communication standard.

This instructor-led live training, available either online or onsite, is designed for advanced participants seeking to comprehend and exploit the emerging synergy between 6G technologies and IoT applications.

Upon completing this course, learners will be able to:

• Articulate the fundamental technical concepts underlying 6G.
• Evaluate how 6G will transform the communication protocols and architecture of IoT devices.
• Analyze 6G-enabled IoT use cases across various industries.
• Develop strategies for incorporating 6G capabilities into current IoT solutions.

Format of the Course

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

Course Customization Options

• For tailored versions of this training aligned with your organizational technology roadmap, please contact us to arrange.

This instructor-led, live training in Turin (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 Turin (online or onsite) is designed for intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI to enhance IoT applications with intelligent data processing and analytics capabilities.

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

• Grasp the fundamentals of Edge AI and its specific applications in IoT contexts.
• Set up and configure Edge AI environments tailored for IoT devices.
• Create and deploy AI models on edge devices for IoT solutions.
• Implement real-time data processing and decision-making mechanisms within IoT systems.
• Integrate Edge AI capabilities with diverse IoT protocols and platforms.
• Address ethical considerations and adhere to best practices for Edge AI in IoT.

This instructor-led, live training in Turin (online or onsite) targets intermediate-level IoT developers, embedded engineers, and AI practitioners who wish to implement TinyML for predictive maintenance, anomaly detection, and smart sensor applications.

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

• Grasp the fundamentals of TinyML and its role in IoT.
• Configure a TinyML development environment tailored for IoT projects.
• Create and deploy ML models on low-power microcontrollers.
• Apply TinyML for predictive maintenance and anomaly detection.
• Optimize TinyML models to balance power efficiency and memory usage.

This instructor-led, live training in Turin (online or onsite) is designed for IT professionals and business managers at an intermediate level who wish to understand how IoT and edge computing can enhance efficiency, enable real-time processing, and foster innovation across various industries.

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

• Grasp the core principles of IoT and edge computing and their significance in digital transformation.
• Recognize specific use cases for IoT and edge computing within manufacturing, logistics, and energy industries.
• Distinguish between edge and cloud computing architectures and their respective deployment contexts.
• Deploy edge computing solutions to support predictive maintenance and real-time decision-making.

Embedded systems are specialized computing devices designed to execute specific tasks within larger frameworks. IoT (Internet of Things) refers to a network of physical devices equipped with sensors and software, enabling them to communicate and share data via the internet.

This instructor-led live training, available either online or on-site, targets technical professionals at the beginner level who aim to grasp and apply embedded systems and IoT concepts using C programming and microcontroller architectures.

Upon completing this training, participants will be capable of:

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

Course Format

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

Customization Options

• To request a customized training session for this course, please contact us to make arrangements.

The primary goal of this training is to clarify the nature of 5G networks and their influence on smart technologies. We will explore both the benefits and drawbacks of the synergy between 5G and the Internet of Things (IoT), while outlining the developmental trajectory of a network ecosystem designed from the outset for the smart world.

Dive deeper into the innovative domain of edge computing with this advanced course. Explore complex architectures and tackle integration challenges, preparing to fully leverage the potential of edge computing across diverse business environments. Gain expertise in cutting-edge tools and methodologies to deploy, manage, and optimize edge computing solutions that address specific industry requirements.

Technological advancements and the exponential growth of data are reshaping operational practices across numerous sectors, including the public sector. Government data generation and 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 becomes more voluminous and complex, the management, processing, storage, security, and retention of this data grow increasingly intricate. New tools for capture, search, discovery, and analysis are enabling organizations to derive valuable insights from unstructured data. The government sector is reaching a critical juncture, recognizing information as a strategic asset. Governments must now protect, leverage, and analyze both structured and unstructured data to fulfill mission requirements and serve the public more effectively. As government leaders work to evolve into data-driven organizations, they are establishing the foundation to correlate dependencies among events, personnel, processes, and information.

High-value government solutions will emerge from the integration of several 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 empowers government entities to make better decisions by acting on patterns identified through the analysis of large volumes of data—both related and unrelated, structured and unstructured.

However, achieving these outcomes requires more than simply accumulating massive amounts of data. As Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy noted in a post on the OSTP Blog, "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."

The White House facilitated agency access to 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 potential is promising. Efficient data storage remains a primary challenge. With budgets often constrained, agencies must minimize storage costs per megabyte while ensuring data remains easily accessible for users to retrieve as needed. Backing up massive data volumes further complicates this task.

Effective data analysis presents another significant challenge. Many agencies utilize commercial tools to sift through vast data sets, identifying trends that enhance operational efficiency. (A recent MeriTalk study indicated that federal IT executives believe Big Data could help agencies save over $500 billion while meeting mission objectives).

Custom-developed Big Data tools are also enabling agencies to meet their analytical 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 routine tasks, such as matching job candidates with hiring managers by reviewing resumes.

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.

Establish a solid foundation in designing and managing resilient edge computing infrastructure. Gain insights into open hybrid cloud infrastructures, managing workloads across diverse cloud platforms, and ensuring flexibility and redundancy. This training provides essential knowledge for creating a scalable and secure infrastructure that supports the dynamic requirements of modern applications through edge computing.

In this instructor-led, live training held in Turin, participants will learn how to maximize Nginx's performance by setting up, configuring, monitoring, and troubleshooting it to handle various forms of HTTP and TCP traffic. The curriculum covers configuring essential Nginx parameters, alongside optimizing the operating system and virtual machine environments to derive the greatest benefit from Nginx.