04-01-2026, 20:39 -
[center]![[Obrazek: 053798272d62962cd8f9bb8dcbcfac85.jpg]](https://i126.fastpic.org/big/2026/0104/85/053798272d62962cd8f9bb8dcbcfac85.jpg)
Iot Application Development: Dashboard, Data Pipelines & Ota
Published 1/2026
Created by Selfcode Academy
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 117 Lectures ( 14h 18m ) | Size: 15.1 GB [/center]
Build real-time IoT dashboards, cloud data pipelines, device management & OTA updates using modern IoT platforms
What you'll learn
Students will learn to Build real-time IoT web dashboards using REST APIs and MQTT over WebSockets to monitor and control connected devices.
Students will able to Design scalable IoT data pipelines using stream processing, data lakes, data warehouses, and cloud-native architectures.
Student will learn to Manage IoT devices at scale with secure provisioning, remote control, monitoring, and over-the-air (OTA) firmware updates.
Students will be able to Analyze and visualize IoT data using Grafana dashboards and understand how AI and ML improve IoT analytics and anomaly detection.
Requirements
Basic understanding of IoT fundamentals and sensors is recommended, but prior cloud or advanced programming experience is not mandatory.
Familiarity with basic programming concepts and internet technologies will help, but everything important is explained step by step.
A computer with internet access and willingness to learn real-world IoT application design is all you need to get started.
No prior experience with dashboards, data pipelines, or OTA updates is required-this course teaches them from scratch.
Description
This course is designed for learners who want to move beyond IoT basics and start building real-world, production-ready IoT applications.In IoT Application Development, you will learn how modern IoT systems are built end-to-end-from connected devices to cloud platforms, real-time dashboards, scalable data pipelines, and secure device management. The course focuses on practical architecture, hands-on workflows, and real use cases used in industry.You'll begin by building IoT web and dashboard applications, understanding the IoT application layer, and designing user interfaces that display live sensor data using REST APIs and MQTT over WebSockets. You will implement command-and-control flows and build a complete smart home dashboard.Next, you'll dive deep into IoT data processing and storage, learning how real-time and batch data pipelines work. You'll explore stream processing, data lakes, data warehouses, Apache Spark, and cloud-native architectures used to handle large-scale IoT data.The course then covers IoT device lifecycle management, including secure device provisioning, monitoring, remote control, and Over-the-Air (OTA) firmware updates. You'll understand how cloud platforms manage devices at scale and implement OTA workflows with real examples.Finally, you'll work with IoT analytics and visualization, building dashboards using Grafana, detecting anomalies in sensor data, and understanding how AI and machine learning enhance IoT systems.What this Course Covers: Module-WiseModule 1: Building IoT Applications (Web & Dashboard UI)This module covers IoT application architecture, the application layer, and how to build web dashboards for real-time sensor data using REST APIs and MQTT over WebSockets. You will design a smart home dashboard with live data and command control.Module 2: Advanced IoT Data Processing & StorageThis module explains how IoT data flows through real-time and batch pipelines. You'll learn stream processing, data lakes, data warehouses, Apache Spark, and how to design scalable cloud IoT data architectures.Module 3: IoT Device Management & OTA UpdatesThis module focuses on managing IoT devices at scale. You will learn device provisioning, authentication, monitoring, remote control, device shadows, and secure OTA firmware updates with real-world cloud workflows.Module 4: IoT Analytics, Visualization & AI ConceptsThis module teaches how to analyze and visualize IoT data using Grafana dashboards. You'll explore anomaly detection, sensor data analytics, and understand how AI and machine learning are applied in modern IoT systems.By the end of this course, you will be able to design, build, and manage complete IoT applications used in smart homes, industrial IoT, and enterprise systems.
Who this course is for
IoT learners who know the basics and want to build real-world IoT applications with dashboards, cloud data pipelines, and device management.
Engineering students and developers aiming to become professional IoT application or solution developers.
Working professionals who want hands-on knowledge of modern IoT architectures used in smart homes and industrial IoT.
Anyone planning a career in IoT, cloud, or data-driven systems and looking to move from theory to practical implementation.
Iot Application Development: Dashboard, Data Pipelines & Ota
Published 1/2026
Created by Selfcode Academy
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 117 Lectures ( 14h 18m ) | Size: 15.1 GB [/center]
Build real-time IoT dashboards, cloud data pipelines, device management & OTA updates using modern IoT platforms
What you'll learn
Students will learn to Build real-time IoT web dashboards using REST APIs and MQTT over WebSockets to monitor and control connected devices.
Students will able to Design scalable IoT data pipelines using stream processing, data lakes, data warehouses, and cloud-native architectures.
Student will learn to Manage IoT devices at scale with secure provisioning, remote control, monitoring, and over-the-air (OTA) firmware updates.
Students will be able to Analyze and visualize IoT data using Grafana dashboards and understand how AI and ML improve IoT analytics and anomaly detection.
Requirements
Basic understanding of IoT fundamentals and sensors is recommended, but prior cloud or advanced programming experience is not mandatory.
Familiarity with basic programming concepts and internet technologies will help, but everything important is explained step by step.
A computer with internet access and willingness to learn real-world IoT application design is all you need to get started.
No prior experience with dashboards, data pipelines, or OTA updates is required-this course teaches them from scratch.
Description
This course is designed for learners who want to move beyond IoT basics and start building real-world, production-ready IoT applications.In IoT Application Development, you will learn how modern IoT systems are built end-to-end-from connected devices to cloud platforms, real-time dashboards, scalable data pipelines, and secure device management. The course focuses on practical architecture, hands-on workflows, and real use cases used in industry.You'll begin by building IoT web and dashboard applications, understanding the IoT application layer, and designing user interfaces that display live sensor data using REST APIs and MQTT over WebSockets. You will implement command-and-control flows and build a complete smart home dashboard.Next, you'll dive deep into IoT data processing and storage, learning how real-time and batch data pipelines work. You'll explore stream processing, data lakes, data warehouses, Apache Spark, and cloud-native architectures used to handle large-scale IoT data.The course then covers IoT device lifecycle management, including secure device provisioning, monitoring, remote control, and Over-the-Air (OTA) firmware updates. You'll understand how cloud platforms manage devices at scale and implement OTA workflows with real examples.Finally, you'll work with IoT analytics and visualization, building dashboards using Grafana, detecting anomalies in sensor data, and understanding how AI and machine learning enhance IoT systems.What this Course Covers: Module-WiseModule 1: Building IoT Applications (Web & Dashboard UI)This module covers IoT application architecture, the application layer, and how to build web dashboards for real-time sensor data using REST APIs and MQTT over WebSockets. You will design a smart home dashboard with live data and command control.Module 2: Advanced IoT Data Processing & StorageThis module explains how IoT data flows through real-time and batch pipelines. You'll learn stream processing, data lakes, data warehouses, Apache Spark, and how to design scalable cloud IoT data architectures.Module 3: IoT Device Management & OTA UpdatesThis module focuses on managing IoT devices at scale. You will learn device provisioning, authentication, monitoring, remote control, device shadows, and secure OTA firmware updates with real-world cloud workflows.Module 4: IoT Analytics, Visualization & AI ConceptsThis module teaches how to analyze and visualize IoT data using Grafana dashboards. You'll explore anomaly detection, sensor data analytics, and understand how AI and machine learning are applied in modern IoT systems.By the end of this course, you will be able to design, build, and manage complete IoT applications used in smart homes, industrial IoT, and enterprise systems.
Who this course is for
IoT learners who know the basics and want to build real-world IoT applications with dashboards, cloud data pipelines, and device management.
Engineering students and developers aiming to become professional IoT application or solution developers.
Working professionals who want hands-on knowledge of modern IoT architectures used in smart homes and industrial IoT.
Anyone planning a career in IoT, cloud, or data-driven systems and looking to move from theory to practical implementation.
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