Internet of Things (IoT) Training in Varna

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

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

• Install and configure n8n for IoT workflow automation.
• Connect IoT devices and platforms utilizing n8n nodes and connectors.
• Develop custom workflows to automate IoT tasks and operational processes.
• Utilize IoT protocols such as MQTT and REST APIs within n8n workflows.
• Monitor, troubleshoot, and optimize IoT automation workflows.

This instructor-led, live training in Varna (online or onsite) is tailored for 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 Varna (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 Varna (online or onsite) is aimed at 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:

• Understand the fundamentals of TinyML and its applications in IoT.
• Set up a TinyML development environment for IoT projects.
• Develop and deploy ML models on low-power microcontrollers.
• Implement predictive maintenance and anomaly detection using TinyML.
• Optimize TinyML models for efficient power and memory usage.

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

Upon completing this training, participants will be able to:

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

The primary goal of this training is to clarify what the 5G network entails and its influence on smart technologies. I aim to illustrate both the benefits and drawbacks of this technological synergy (5G / IoT) and outline the development trajectory of the network, which has been oriented toward the smart world from its inception.

This hands-on course offers a thorough introduction to the Internet of Things (IoT), spanning from device-level programming to cloud-based data processing and visualization. Participants will examine the entire IoT architecture—including sensors, communication protocols, microcontrollers, and cloud integration—through guided exercises utilizing development boards such as ESP32 and Raspberry Pi. Upon completing the course, learners will be equipped to construct a full IoT pipeline: capturing sensor data, transmitting it via MQTT/HTTP, processing it on cloud platforms like Azure IoT Hub, AWS IoT Core, or Google Cloud IoT, and visualizing it using tools such as Grafana or Power BI. The curriculum also addresses security best practices and simulated cyber threats to guarantee secure and robust deployments.

In this instructor-led, live training conducted Varna, participants will learn how to maximize Nginx's performance by setting up, configuring, monitoring, and troubleshooting it to manage various forms of HTTP and TCP traffic. The curriculum covers the configuration of critical Nginx parameters, along with OS and virtual machine adjustments, to ensure optimal utilization of Nginx.