A live computer vision course with Python for students who want to teach computers to see. You start with pixels and OpenCV, then move to object detection with YOLO and deep learning. Small batches, Hinglish classes and mentor review on every assignment.
At a glance
Tools
Who it's for
Before you start
Outcomes
Real skills you can show — every project goes on your GitHub.
Syllabus
Each module has a clear goal, live classes, a lab session and practice you push to GitHub. Your mentor reviews it and tells you exactly how to improve.
Module 1
Load and inspect images in code and understand how they are stored.
PythonOpenCVNumPy
Practice: Photo tool that resizes and converts a folder of images
Module 2
Clean and prepare images with classic filters.
OpenCV
Practice: Document scanner that straightens a photo of a page
Module 3
Use non-deep-learning methods for detection and segmentation.
OpenCV
Practice: Simple webcam face counter
Module 4
Train and reuse CNNs for image classification.
PyTorchTensorFlowKeras
Practice: Image classifier on a small custom dataset
Module 5
Detect and label several objects in images and video.
Ultralytics YOLOOpenCV
Practice: Detect helmets or masks in photos
Module 6
Read text from images and use vision systems carefully.
TesseractOpenCV
Practice: Read text from photos of notices or bills
Module 7
Build and present two complete vision projects.
GitGitHub
Practice: Face mask detector · OCR tool · Licence plate recognition
Projects
Pick one, plan it like a real team with tickets, build it, and present it. It becomes the centrepiece of your portfolio.
Detect whether people in photos or webcam video wear masks, and measure where it makes mistakes.
Read printed text from photos with Tesseract and OpenCV pre-processing, and measure its accuracy.
Find a number plate with a detector and read it with OCR. Use only your own or public sample images.
Opening soon
This specialisation isn't scheduled yet. Join the waitlist and we'll tell you first when a batch opens. We open the courses with the most interest first.
Where it can lead
Roles this skill helps you towards
No course can guarantee a job. We help you build real skills, real projects and a portfolio you can show.
FAQ
The batch is not scheduled yet. Join the waitlist and we will tell you first when dates are fixed.
A laptop webcam is enough for the live demos. Training runs on free Google Colab, so you do not need a GPU.
No. We teach the CNN basics we need inside the course. A prior deep learning course makes it easier but is not required.
If you are comfortable with Python and like projects, you can try it. Image processing in the first modules is quite visual and friendly.
We use only your own photos, consented photos or public sample datasets. We also discuss privacy and why these systems need care.
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