Edge Computing Fundamentals Course in chennai

825 Ratings

Master edge computing, distributed computing, IoT edge architecture, real-time data processing, and cloud-edge integration with Edubrights’ EDGE COMPUTING – Architecture & Implementation training in Chennai. This course is designed for students, freshers, cloud engineers, IoT developers, software developers, DevOps engineers, network engineers, solution architects, and working professionals who want to design, deploy, and manage modern edge computing solutions.

Gain hands-on experience with edge devices, edge gateways, containerized workloads, edge AI, IoT connectivity, orchestration, security, monitoring, and real-world edge computing implementation projects through practical industry use cases.

Key Highlights:

✅ Real-Time Edge Computing Projects & Distributed Systems Use Cases

✅ Live Instructor-Led Training by Experienced Edge Computing Experts

✅ Hands-On Practice with Edge Computing Platforms & Infrastructure

✅ Edge Computing Fundamentals, Architecture & Distributed Computing Concepts

✅ Edge Devices, Gateways, Sensors & IoT Ecosystem Integration

✅ Edge Data Processing, Real-Time Analytics & Low-Latency Computing

✅ Containerization, Docker, Kubernetes & Edge Orchestration

✅ Edge AI, Machine Learning Inference & Intelligent Automation

✅ Edge Networking, Communication Protocols & Cloud Connectivity

✅ Security, Identity Management, Device Authentication & Data Protection

✅ Performance Optimization, Monitoring, Troubleshooting & Edge Deployment Best Practices

✅ Integration with AWS IoT Greengrass, Microsoft Azure IoT Edge, Google Distributed Cloud Edge, Kubernetes, Docker, MQTT, Raspberry Pi, NVIDIA Jetson & REST APIs

✅ Resume Building, Portfolio Development & Mock Interview Preparation

✅ Career Guidance, Placement Assistance & Edge Computing Certification Support

✅ Flexible Online, Classroom & Weekend Training Options

✅ Corporate Training for IoT, Manufacturing, Telecommunications, Healthcare, Smart Cities & Enterprise IT Teams

Build practical edge computing expertise, design scalable distributed systems, deploy intelligent edge applications, optimize real-time data processing, and become industry-ready for careers in Edge Computing, IoT Development, Cloud Engineering, DevOps, Embedded Systems, AI at the Edge, and Enterprise Infrastructure.

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₹35000

₹42000

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Case Studies and Projects

Hours of Training

20+

Placement Assurance

100%

Expert Support

Yes

Support & Access

Lifetime

Certification

Yes

Skill Level

All

Language

All

Course Objectives

Q1. How does computing happen closer to data sources?

You will understand the core concepts of Edge Computing and its advantages over traditional cloud computing.

Q2. How do you deploy applications at the edge?

You will learn to run workloads on edge devices, gateways, and local servers.

Q3. How do you ensure low latency and real-time processing?

You will implement edge solutions for IoT, autonomous systems, and time-sensitive applications.

Q4. How do you manage security and data at the edge?

You will address security challenges and best practices for edge environments.

Q5. How do you prepare for future technology roles?

You will gain foundational skills in Edge Computing for emerging tech careers.

Popular Techniques Covered in This Course

Edge Computing concepts and architecture

Edge vs Cloud vs Fog Computing

Working with edge devices and gateways

Deploying applications at the edge

IoT integration with edge computing

Real-time data processing

Edge security and privacy

Monitoring and managing edge nodes

Containerization at the edge

Use cases in industry

Get Hands-on Knowledge about Real-Time Projects

Project 1

Project 1: Smart Factory Edge Solution

Deploy an edge computing system for real-time machine monitoring.

Project 2

Project 2: Video Analytics at the Edge

Build a system for real-time video processing using edge devices.

Project 3

Project 3: IoT Data Processing Pipeline

Create an edge solution for collecting and processing sensor data locally.

Project 4

Project 4: Edge Security Implementation

Secure an edge environment with proper authentication and encryption.

Project 5

Project 5: Autonomous System Simulation

Develop a basic edge computing use case for autonomous decision-making.

Key Features

Edubrights offers EDGE COMPUTING – ARCHITECTURE & IMPLEMENTATION Training in virtual mode with expert trainers. Here are the key features,

40 Hours Course Duration

100% Job Oriented Training

Industry Expert Faculties

Free Demo Class Available

Completed 500+ Batches

Certification Guidance

Curriculum

Module 1: Introduction to Edge Computing

Edge computing vs cloud computing: latency, bandwidth, and data sovereignty
Edge computing architecture: devices, edge nodes, and cloud tiers
Use cases: autonomous vehicles, smart manufacturing, video analytics, and 5G
Edge computing platforms: AWS Greengrass, Azure IoT Edge, and Google Anthos

Module 2: AWS IoT Greengrass

AWS Greengrass v2 architecture: core device, components, and cloud integration
Deploying Greengrass on edge devices: Linux and containerised deployments
Greengrass components: Lambda functions, Docker containers, and ML models
Local messaging: MQTT bridge and inter-process communication

Module 3: Azure IoT Edge

Azure IoT Edge architecture: IoT Edge runtime, modules, and IoT Hub
Deploying custom modules: Docker containers as IoT Edge modules
Edge routing: message routing between modules and to IoT Hub
Azure Stream Analytics on Edge for local data processing

Module 4: Containerised Edge Workloads

Docker on edge devices: deploying lightweight containers
K3s and MicroK8s: lightweight Kubernetes for edge orchestration
Helm charts for edge application deployment and management
Multi-node edge clusters: managing distributed edge infrastructure

Module 5: Machine Learning at the Edge

Edge ML frameworks: TensorFlow Lite and ONNX Runtime
Model optimisation: quantisation and pruning for edge deployment
NVIDIA Jetson: GPU-accelerated edge inference for computer vision
AWS SageMaker Edge Manager and Azure ML edge deployment

Module 6: Edge Networking and Connectivity

5G and edge computing: MEC (Multi-access Edge Computing)
Network protocols for edge: MQTT, CoAP, and OPC-UA
SD-WAN for reliable and secure edge site connectivity
Edge data synchronisation: managing intermittent connectivity

Module 7: Edge Security and Management

Zero-trust security model for distributed edge environments
Certificate management and device identity at scale
Remote monitoring and OTA updates for edge deployments
Observability: logging, metrics, and tracing at the edge

Module 8: Capstone Project and Assessment

AWS Greengrass or Azure IoT Edge deployment on an edge device
Containerised ML inference pipeline at the edge
Edge security configuration and remote management setup
Final assessment and course certification

Receive Training From Our Skilled and Effective Trainers

Experience in the Industry Learn from edge computing architects who have designed distributed edge infrastructure for smart manufacturing plants, retail analytics deployments, and telecommunications edge computing platforms.

Backgrounds at the Top Our edge computing trainers have worked at cloud providers, industrial IoT companies, and systems integrators delivering edge solutions that bring compute closer to where data is generated.

Clear & Effective Teaching Edge computing architecture, AWS Greengrass, Azure IoT Edge, containerised edge workloads, ML at the edge, 5G MEC, edge security, and remote management are taught with real edge deployment examples.

Hands-On Learning Focus Students deploy AWS Greengrass or Azure IoT Edge, containerise workloads, run ML inference at the edge, configure edge security, and set up remote monitoring through structured hands-on lab exercises.

Up-to-Date Knowledge Trainers keep content current with the latest AWS Greengrass and Azure IoT Edge releases, NVIDIA Jetson platform updates, emerging 5G edge use cases, and evolving edge computing architecture best practices.

About Our Course Certification*

Our institution offers a recognized Edge Computing Fundamentals certification. This certification enhances your portfolio and prepares you for collaborative projects in real-world environments. Gain practical skills through hands-on training and assessments.