Description

Course Description:

The Edge Computing with IoT is designed to give learners a strong understanding of how smart devices process and analyze data closer to the source, enabling faster decision-making and reduced latency. This course covers the architecture, protocols, and security essentials of IoT devices deployed at the network edge. Students will learn how to integrate sensors, microcontrollers, and cloud-edge frameworks to build scalable, real-time IoT applications used in industries like smart cities, manufacturing, and healthcare. By the end of the program, participants will be able to develop end-to-end edge-enabled IoT solutions and optimize system performance for real-world deployments.

Key Features of Course Divine:

• Collaboration with E‑Cell IIT Tirupati
• 1:1 Online Mentorship Platform
• Credit-Based Certification
• Live Classes Led by Industry Experts
• Live, Real-World Projects
• 100% Placement Support
• Potential Interview Training
• Resume-Building Activities

Career Opportunities After Edge Computing with Iota Certified Course:

• IoT Edge Developer
• Edge Computing Engineer
• IoT Solutions Architect
• Embedded Systems Engineer
• Cloud & Edge Integration Specialist
• Smart Device Application Developer
• Industrial IoT (IIoT) Engineer
• IoT Security Specialist
• Data Analyst for IoT Systems
• Network & Connectivity Engineer

Essential Skills you will Develop Edge Computing with Iota Certified Course:

• Designing and deploying edge-enabled IoT systems
• Programming microcontrollers and edge devices
• Working with IoT communication protocols (MQTT, CoAP, etc.)
• Real-time data processing & analytics at the edge
• Cloud to edge integration and device management
• IoT network security and encryption techniques
• Sensor interfacing and data acquisition
• Performance optimization for low-latency systems
• Troubleshooting and maintaining IoT devices
• Building scalable and intelligent IoT solutions

Tools Covered:

• Raspberry Pi / Arduino
• Edge AI Frameworks (TensorFlow Lite / OpenVINO)
• IoT Protocols & Platforms (MQTT, CoAP, AWS IoT Core, Azure IoT Hub)
• Sensors & Actuators Integration Tools
• Microcontroller Programming (C/C++ & Python)
• Docker & Containerization for Edge Deployment
• Node-RED for IoT Workflows & Automation
• Linux OS & Shell Scripting
• Grafana / Kibana for Edge Data Visualization
• Git & Version Control

Syllabus:

MODULE 1: Fundamentals of IoT Introduction to IoT concepts IoT architecture & components Sensors, actuators & embedded systems IoT communication models (Device–Device, Device–Cloud, etc.).

MODULE 2: Introduction to Edge Computing What is Edge, Fog & Cloud computing Need for edge computing in IoT Comparison: Cloud vs Fog vs Edge Real-world use cases & benefits.

MODULE 3: IoT Communication Protocols MQTT, CoAP, AMQP overview HTTP/HTTPS vs lightweight protocols Pub/Sub architecture Message brokers

MODULE 4: Edge Devices & Hardware Platforms Raspberry Pi, NVIDIA Jetson, Arduino, ESP32 Gateways & edge servers Hardware interfacing Device provisioning & management.

MODULE 5: Edge AI & Data Processing Data filtering, aggregation & analytics at edge AI/ML model deployment at edge TinyML fundamentals Real-time decision making at the edge.

MODULE 6: Edge Software Frameworks EdgeX Foundry AWS IoT Greengrass Azure IoT Edge Kubernetes for edge workloads Containerization & Docker on edge devices.

MODULE 7: Networking & Connectivity Wi-Fi, Bluetooth, Zigbee, LoRaWAN, 5G Edge-to-cloud connectivity Network latency & bandwidth optimization Edge mesh networks.

MODULE 8: Edge Security & Compliance Device authentication & authorization Secure communication protocols Data protection at edge devices Threat detection & intrusion prevention.

MODULE 9: Edge-Oriented IoT Architecture Design Distributed IoT architectures Designing low-latency solutions Event-driven edge systems Scalability & resilience in edge deployments.

MODULE 10: Hands-on Projects & Deployment Building IoT edge pipeline (sensor → edge → cloud) Deploying AI model on edge device Connecting edge devices to cloud platforms Capstone live project & documentation.

Industry Projects:

• Smart Home Automation System with Edge Control
• Real-Time Industrial Machine Health Monitoring
• Smart Agriculture Irrigation Using Edge Analytics
• Smart City Traffic Monitoring with Low-Latency Alerts
• Edge-Based Healthcare Wearable Data Processing
• Automated Energy Management System for Buildings

Who is this program for?

• Engineering and diploma students interested in IoT and smart technologies
• Working professionals transitioning to IoT or embedded domains
• Developers aiming to build real-time edge-enabled applications
• Electronics, Computer Science, and IT graduates seeking industry skills
• Tech enthusiasts who want hands-on experience with IoT devices
• Professionals in industries like automation, manufacturing, and utilities

How To Apply:

Mobile: 9100348679

Email: coursedivine@gmail.com