AI and machine learning · Free online course

Computer Vision with OpenCV

Classical image processing on the pictures a plant produces: parts on a belt, caps on bottles, a scratch on a surface. Images as arrays, thresholds, morphology, edges, contours and measurement, video and background subtraction, tracking and counting, Hough and template matching, and the camera, lens and lighting decisions that come before any code.

  • 12 modules
  • 15h 5m of video
  • Beginner
  • English
  • ₹0, free
  • Lab practice in your browser
Computer Vision with OpenCV course cover

₹0Free for good

Worth ₹6,999 by length and depth against classroom training. It has always been free; that is not a former price.

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Overview

About Computer Vision with OpenCV

Learn classical image processing in OpenCV on plant pictures: thresholds, edges, contours, measuring, tracking and counting.

Computer Vision with OpenCV is a free, self-paced online course from EDWartens for engineers, developers and students applying AI to real work. It has 12 modules and 15h 5m of video lessons by ProgrammingKnowledge, Murtaza's Workshop, freeCodeCamp.org and others, with written notes and worked problems, a practical project with a document pack and a 15-question final assessment (pass mark 60%). Learning is free with an account; an optional certificate with a public verification code is issued when you pass. Last updated 27 September 2026.

Who it is for: Engineers, developers and students applying AI to real work

This course includes

  • 15h 5m of video lessons
  • 12 modules with written notes and diagrams
  • One final assessment: 15 questions, pass mark 60%
  • Ask-an-engineer support from practising engineers
  • Lifetime access, the course does not expire
  • Optional verifiable certificate when you finish
  1. Step 1 of 3

    Learn the 12 modules

    15h 5m of video lessons, written notes and a practice task per module, at your own pace.

  2. Step 2 of 3

    Pass the final assessment

    15 questions drawn from every module, pass mark 60%, 3 attempts.

  3. Step 3 of 3

    Take the certificate, if you want it

    Optional, paid once, only if you choose it. The course stays free either way.

    See the certificate and its price

A look inside

Computer Vision with OpenCV: Syllabus at a glance
Syllabus at a glance
Computer Vision with OpenCV: What you will be able to do
What you will be able to do
Computer Vision with OpenCV: Tools and credits
Tools and credits

From the lessons

  • OpenCV Python Tutorial For Beginners 1 - Introduction to OpenCV

    An image is an array

    by ProgrammingKnowledge

  • OpenCV Python Tutorial For Beginners 5 - Draw geometric shapes on images using Python OpenCV

    Drawing, arithmetic, masks and HSV colour

    by ProgrammingKnowledge

  • OpenCV Python Tutorial For Beginners 14 - Simple Image Thresholding

    Thresholding and morphology

    by ProgrammingKnowledge

  • OpenCV Python Tutorial For Beginners 18 - Smoothing Images | Blurring Images OpenCV

    Smoothing, gradients and Canny edges

    by ProgrammingKnowledge

  • OpenCV Python Tutorial For Beginners 23 - Find and Draw Contours with OpenCV in Python

    Contours, shapes and measurement

    by ProgrammingKnowledge

  • OpenCV Python Tutorial For Beginners 4 - How to Read, Write, Show Videos from Camera in OpenCV

    Video, motion and background subtraction

    by ProgrammingKnowledge

Lesson frames belong to the creators named in the Credits and are shown from YouTube.

What you learn

What you will be able to do

By the end you will be able to:

  • Read, convert, crop and measure images in OpenCV
  • Threshold and clean binary images
  • Find contours and turn them into counts and millimetre measurements
  • Subtract background and track objects across a counting line
  • Choose cameras, lenses and lighting

How it works

How this course works

  1. Watch the lessons

    Short video lessons, one module at a time, at your own pace.

  2. Read the notes

    Open the Reading tab for the written notes and diagrams of the module.

  3. Practise in the 3D labOptional

    Try the module in the free 3D lab, in your browser.

  4. Check yourself

    Answer the questions to see what stuck before you move on.

  5. Final assessment

    Pass the final once you have been through the modules.

  6. Certificate, if you want oneOptional

    Optional, with a page anyone can use to verify it.

Syllabus

Course content, module by module

In order, at whatever pace suits you. Each module ends with a practice task that builds on the last.

Modules
12
Video lessons
34
Of video
15h 5m
Final questions
15
  1. 01

    An image is an array

    2 lessons · 24m
  2. 02

    Drawing, arithmetic, masks and HSV colour

    5 lessons · 1h 25m
  3. 03

    Thresholding and morphology, with lab practice:

    3 lessons · 45m
  4. 04

    Smoothing, gradients and Canny edges

    3 lessons · 40m
  5. 05

    Contours, shapes and measurement, with lab practice:

    2 lessons · 30m
  6. 06

    Video, motion and background subtraction

    3 lessons · 49m
  7. 07

    Tracking and counting across a line

    2 lessons · 27m
  8. 08

    Histograms, template matching and Hough

    5 lessons · 1h 11m
  9. Final assessment · 15 questions, pass mark 60%

3D lab

Practise in the 3D lab

Tune the same ideas you code in OpenCV, a region, a threshold and a blob size, on a camera inspecting parts in the AI Workbench, and measure the false rejects.

Train and testWatch

Optional. Skip it whenever you like: it never blocks your progress or your certificate.

Project

The course project

Optional practice that ends in the kind of job the course prepares you for, with the documents that go with it.

About 7 hours

Count parts on a conveyor: a synthetic belt with known truth, then your own video

Build a part counter from detection, morphology, contours, a centroid tracker and a counting line. Debug it on a synthetic belt video whose true count you know. Then run it on thirty seconds of your own phone footage and report misses and double counts separately.

This project at a glance
  1. 8documents in the pack
  2. 7steps to follow
  3. 6things to hand in
  4. 7 hof work, at your pace

Sample document pack, 8 documents, filled in for the scenario

  • PlanProject plan: camera count check on PET line 3
  • FDSFunctional design: part counter pipeline and parameters
  • DatasheetTest video datasheet: bench and site
  • DatasheetCamera and lighting specification for line 3 (stage 3 input)
  • ProcedureTest procedure: counting against ground truth
  • Test reportTest record: bench and site trials of the part counter
  • RegisterCount-error and change register
  • ReportProof-of-concept report: camera count check for line 3

Read inside the course and download as a workbook. The project is optional practice, marked when you submit it; the certificate needs only the modules and the final assessment.

About 4 hours

Sort bottle caps by colour and check their size, from your own photos

Photograph a tray of mixed bottle caps (or any small coloured parts) under fixed light. Detect each cap by HSV colour. Measure its diameter in millimetres against a ruler in the frame. Produce a table and an annotated image. This is a two-station inspection in one script.

This project at a glance
  1. 7documents in the pack
  2. 6steps to follow
  3. 6things to hand in
  4. 4 hof work, at your pace

Sample document pack, 7 documents, filled in for the scenario

  • PlanProject plan: bench demonstration of colour sort and size check for closures
  • URSRequirements for the bench colour and size check
  • ProcedureProcedure: photographing the tray and measuring the scale
  • RegisterColour range register: HSV limits and the light they were tuned under
  • Test reportTest record: colour count and diameter check on five photos
  • RegisterMeasurement register: reference caps and photo totals
  • ReportBench demo report: colour sort and size check

Read inside the course and download as a workbook. The project is optional practice, marked when you submit it; the certificate needs only the modules and the final assessment.

Tools

Software, hardware and lessons

Software

Google Colab (free) with OpenCV pre-installed. A phone camera for the projects.

Hardware

A phone camera, a tray and a ruler for the projects. No industrial camera needed.

Who it is for

Beginner in vision. Needs basic Python and NumPy — the Python for AI course, or equivalent.

Video lessons by

  • ProgrammingKnowledge
  • Murtaza's Workshop
  • freeCodeCamp.org
  • SmartVisionLights
  • Nicolai Nielsen

Independent creators, credited in full under Credits.

Software you need

What to download, where from, what it costs and how to install it. Every link goes to the maker's own site, never a mirror.

OpenCV is already installed in Colab. A phone camera is enough for the projects.

Required

  1. 01

    Google Colab

    Google, in the browser

    Free, GPU time not guaranteed
    Runs on
    Any modern web browser
    Account
    A free Google account

    Colab is free to use. In the free version GPUs and TPUs are heavily restricted and not guaranteed, sessions can run for at most 12 hours, and idle sessions are stopped. Paid plans give more reliable access.

    Open Google Colabcolab.research.google.com

Optional

Useful, not needed to finish the course.

  1. 02

    OpenCV (opencv-python)

    OpenCV, a Python or npm package

    Free
    Runs on
    Windows, macOS and Linux with Python 3
    Account
    None needed

    Free, open source under the Apache 2.0 licence.

Checked against each maker's own page on 27 September 2026. Trial lengths and editions change; the maker's page is the final word.

What you walk away with

Your certificate for Computer Vision with OpenCV

Finish the course, pass the final, and this is the document with your name on it.

Sample Wartens Certificate of Completion for Computer Vision with OpenCV, issued through the EDWartens training portal
Sample. The issued certificate carries your name, your final score, a unique certificate ID and its own QR code.
  • Verifiable by anyone

  • Adds to LinkedIn in one click

  • QR code on the certificate

  • Names what you can do

  • A permanent link

  • Earned, not attended

Learning is free. The certificate is optional.

Add it now and pay only when you have finished the course, or come back for it later. One-off, US$23.99, with a receipt.

Issued by Wartens Ltd (England and Wales, company no. 15262249) through the EDWartens training portal, as a Certificate of Completion for this self-paced course. Sold in India by Wartens Automation Private Limited. It is not a vendor certification, a university award or a CPD-accredited activity, and it does not certify competence on live equipment. Delivered electronically; see the refund policy.

Practise what you learn in the free 3D lab

Technical work is judged on what you can do: wiring, commissioning, finding a fault. Doing a task yourself teaches more than watching it a second time, and a lab lets you try it safely before you meet real equipment. It does not replace working on real hardware.

  • Practise safely, so a mistake costs nothing.
  • The lab checks your work like a site test, so you know when it is right.
  • Free, in your browser, with nothing to install.

Why learn with EDWartens

What you get with this course.

  • Free from the first lesson to the final assessment.
  • Practice in a free 3D lab in your browser, with nothing to install.
  • Video lessons with written notes and a project.
  • An optional certificate that anyone can verify online.

FAQ

Common questions

Do I need an industrial camera?

No. Every exercise runs on images and videos you make with a phone, plus a synthetic belt video the notebook generates with a known part count. The module on cameras and lighting tells you what to buy when the time comes.

Is this deep learning?

No, and deliberately. This course is the classical toolbox that solves most fixed-camera inspection jobs at a fraction of the cost. The Deep Learning and Machine Vision courses build on it. It also teaches you to measure when classical methods fail. Then a neural network is a decision, not a reflex.

What are the projects in the Computer Vision with OpenCV course?

There are two projects. The first is a conveyor part counter with detection, tracking and a counting line. You debug it on a synthetic belt video with a known count, then run it on your own phone video. Misses and double counts are reported separately. The second is a colour-sorting and size-check station on photos of bottle caps.

Is the Computer Vision with OpenCV course really free?

Yes. Every module, practice task, project and assessment. You create an account so your progress is saved and the assessments can be marked. The certificate is the only paid item, and only if you want it.

What certificate does the Computer Vision with OpenCV course give?

An EDWartens Certificate of Completion, issued when you have finished the modules and passed the final assessment (the project is optional practice), with a verification code anyone can check. It is not a vendor credential and is never described as one.

Who made the video lessons in the Computer Vision with OpenCV course?

The creators named in the Credits block at the foot of this page, on their own YouTube channels. EDWartens did not make the videos and the creators are not affiliated with EDWartens. What EDWartens wrote is the study plan, the notes, the practice tasks, the projects and the assessments.

How long does the Computer Vision with OpenCV course take?

Plan on about 19 hours in all, including the video lessons, notes and practice tasks. It is self-paced, so you work through the twelve modules at your own speed.

Do I have to use the lab?

No. The lab is optional practice. You can skip it whenever you like, and it never blocks your progress, the final assessment or your certificate.

Is the lab free?

Yes. Every lab level for this course opens in your browser, free, with nothing to install.

Is the Computer Vision with OpenCV course free in India, and what does the certificate cost?

Yes. Learning costs ₹0 in India: every module, the written notes, the practice tasks and the final assessment, with no card and no trial period. The only paid item is the optional EDWartens Certificate of Completion, ₹499 including GST for this beginner course, paid in rupees through Razorpay, and only if you want it after passing the final assessment.

All course facts
Price
₹0, free for good. No trial, no card. Comparable classroom training of this length costs about ₹6,999.
Who it is for
Engineers, developers and students applying AI to real work
Format
12 self-paced modules, 15h 5m of video, written notes, a practice task per module and one final assessment.
Level
Beginner. Beginner in vision. Needs basic Python and NumPy — the Python for AI course, or equivalent.
Brand
Vendor-neutral
Software
Google Colab (free) with OpenCV pre-installed. A phone camera for the projects.
Hardware
A phone camera, a tray and a ruler for the projects. No industrial camera needed.
Certificate
Optional EDWartens Certificate of Completion, ₹499 inclusive of GST for learners in India, verifiable by code. Not a vendor credential.
Video lessons by
ProgrammingKnowledge, Murtaza's Workshop, freeCodeCamp.org, SmartVisionLights, Nicolai Nielsen (independent creators, credited below)
Language
English
Last updated
27 September 2026

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Credits

Who made the video lessons

The video lessons in this course were created by the people below, not by EDWartens. Every lesson streams from its creator's own YouTube channel; EDWartens neither hosts nor sells that footage, and the creators are not affiliated with EDWartens and do not endorse this course. What EDWartens wrote is the study plan, the notes, the practice tasks and the assessments.

If you are one of these creators and would like a lesson removed or credited differently, write to info@wartens.com.