What is the duration of the Computer Vision course in Chennai?

The Computer Vision course is 3 months long with live sessions and hands-on labs. Weekend batches are also available.

What tools will I learn in the Computer Vision course?

You will learn OpenCV, YOLO (v5 and v8), TensorFlow, Keras, MediaPipe and Hugging Face Vision Transformers.

What projects will I build in the Computer Vision course?

You will build a real-time face recognition system, vehicle detection dashboard, medical image classifier and a gesture-controlled interface.

Is Computer Vision in demand in Chennai?

Yes. Computer Vision engineers are in high demand across manufacturing, healthcare, retail and autonomous systems sectors in India.

Can beginners join the Computer Vision AI course?

Basic Python and some exposure to Deep Learning is recommended. If you are a complete beginner, we suggest starting with our Python or AI/ML course first.

👁 Computer Vision Track

Computer Vision Course in Chennai — OpenCV, YOLO & Deep Learning

Master image recognition, object detection, and video analysis. Build the vision AI systems used in autonomous vehicles, medical imaging, and surveillance.

View Syllabus ↓

7 Modulescovered

5+ Projectsbuilt

OpenCV + TensorFlowtools

CV Engineeroutcome

📚 Course Syllabus

Computer Vision Skills You'll Master

Every module is outcome-driven — you build something real at the end of each one.

OpenCV basicsPixel operationsColor spacesFiltersEdge detection

Load, manipulate, and display images with OpenCV

Apply Gaussian blur, Sobel, and Canny filters

Convert between color spaces (BGR, HSV, Gray)

Process and manipulate any image with code

Conv2DMaxPoolingFlattenDenseReLUSoftmax

Build CNN architecture from scratch

Train on MNIST and CIFAR-10

Understand feature map visualization

Build image classifiers achieving 95%+ accuracy

VGG16ResNet50InceptionV3MobileNetFine-tuningFeature extraction

Apply pretrained models to new domains

Fine-tune the last layers for custom classes

Achieve state-of-the-art results with minimal data

Build high-accuracy classifiers with limited training data

YOLOSSDAnchor boxesIoUNMSCOCO dataset

Detect and localize multiple objects in images

Train YOLO on custom datasets

Evaluate with mAP metric

Build real-time object detectors for custom use cases

U-NetFCNPixel-wise classificationMedical imagingMask RCNN

Segment every pixel in an image

Apply U-Net to medical scan datasets

Build instance segmentation pipelines

Build pixel-level understanding models

Video captureFrame processingOptical flowAction recognitionWebcam AI

Process video streams frame-by-frame

Detect motion and track objects

Build real-time applications with webcam

Build live video AI systems that run in real time

ONNXTensorRTFastAPIStreamlitEdge deploymentDocker

Optimize models for inference speed

Serve vision models via API

Deploy to edge devices and cloud

Deploy vision AI to production and edge devices

🛠 Tech Stack

Computer Vision Tools & Frameworks

Industry-standard tools you'll use throughout this program — exactly what employers want.

👁

OpenCV

Image processing

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TensorFlow

Model training

🎯

YOLO

Object detection

🤗

HuggingFace

Vision models

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FastAPI

API serving

🎯

Streamlit

App deploy

📦

ONNX

Model optimization

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Docker

Containerization

💻 Real Projects

Vision AI Projects You'll Build

Portfolio-ready projects that demonstrate your skills to recruiters from day one.

PROJECT 01

Real-Time Face Mask Detector

Detect whether people are wearing masks in live webcam feed using YOLO.

OpenCVYOLOTensorFlowPython

✅ Live real-time detection running at 30fps

PROJECT 02

Medical Image Classifier

Classify chest X-rays as normal or pneumonia using transfer learning.

ResNet50TensorFlowPandasStreamlit

✅ 93%+ accurate medical imaging tool

PROJECT 03

Custom Object Detector

Train YOLOv8 to detect custom objects from scratch with your own dataset.

YOLOv8OpenCVLabelImgPython

✅ Custom-trained detector deployable anywhere

PROJECT 04

Document Scanner App

Auto-detect and straighten document borders from camera images.

OpenCVNumpyPerspective transformStreamlit

✅ Mobile-ready document scanning app

🎯 Transformation

Vision AI Roles You'll Land

By the end of this program, you won't just have knowledge — you'll have career-changing proof.

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CV Engineer

Build vision AI for autonomous systems

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Medical AI

Apply CV to healthcare and diagnostics

🎥

Video AI

Process live video feeds in real time

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Robotics Ready

Foundation for robotics and autonomous vehicles

🏢 Placement Network

Our Students Work Here

⚡ Next Batch Closing Soon — Limited Seats

Start Your AI Journey Today

Join Computer Vision and build real-world skills that get you hired.

🔒 2-day risk-free trial · 30-day money back · No credit card required

Frequently Asked Questions

About the Computer Vision Course in Chennai

The Computer Vision course is 3 months long covering image processing, object detection with YOLO, face recognition and deployment with TensorFlow.

You will learn OpenCV, YOLO, TensorFlow, PyTorch, Mediapipe and Streamlit to build and deploy real-time computer vision AI systems.

Basic Python knowledge is helpful. The course covers necessary Python and deep learning fundamentals before OpenCV, YOLO and advanced vision AI topics.

Computer vision engineers in Chennai earn ₹8–18 LPA at entry level. Specialists with YOLO, TensorFlow and real-time detection skills can earn ₹25 LPA and above.

You will build an image classifier, object detection system, face recognition app, gesture control interface and a real-time video analytics pipeline.