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
₹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
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.
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
- 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.
- Step 2 of 3
Pass the final assessment
15 questions drawn from every module, pass mark 60%, 3 attempts.
- 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
From the lessons
An image is an array
by ProgrammingKnowledge
Drawing, arithmetic, masks and HSV colour
by ProgrammingKnowledge
Thresholding and morphology
by ProgrammingKnowledge
Smoothing, gradients and Canny edges
by ProgrammingKnowledge
Contours, shapes and measurement
by ProgrammingKnowledge
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
Read, convert, crop and measure images in OpenCV; detect by colour in HSV; threshold and clean binary images; find edges and contours and turn them into counts and millimetre measurements; process video, subtract background and track objects across a counting line; use histograms, template matching and Hough transforms; choose cameras, lenses, lighting and triggers; and evaluate a counter against ground truth.
- Treat an image as an array and measure a part in millimetres from pixels
- Detect parts by colour in HSV and by brightness with Otsu and adaptive thresholds
- Clean binary images with morphology and separate touching parts
- Find contours and turn them into counts, sizes, shapes and pass/fail
- Process video, subtract the background and count parts crossing a line with a tracker
- Choose camera, lens, lighting and trigger so the software stays simple
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
- 01
An image is an array
2 lessons · 24m - 02
Drawing, arithmetic, masks and HSV colour
5 lessons · 1h 25m - 03
Thresholding and morphology
3 lessons · 45m - 04
Smoothing, gradients and Canny edges
3 lessons · 40m - 05
Contours, shapes and measurement
2 lessons · 30m - 06
Video, motion and background subtraction
3 lessons · 49m - 07
Tracking and counting across a line
2 lessons · 27m - 08
Histograms, template matching and Hough
5 lessons · 1h 11m Final assessment · 15 questions, pass mark 60%
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 — 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.
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, and produce a table and an annotated image — a two-station inspection in one script.
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
- 01Free, GPU time not guaranteed
Google Colab
Google, in the browser
- 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.
Steps
- 1.Open colab.research.google.com and sign in with your Google account.
- 2.Click New notebook (or open the notebook your course links to).
- 3.For a GPU, choose Runtime, then Change runtime type, then pick a GPU if one is offered.
- 4.Type code in a cell and press Shift and Enter to run it.
- Save a copy to your Google Drive so your changes are kept.
- Files on the runtime are deleted when the session ends. Save outputs to Drive.
Open Google Colabcolab.research.google.com
Optional
Useful, not needed to finish the course.
- 02Free
OpenCV (opencv-python)
OpenCV, a Python or npm package
- Runs on
- Windows, macOS and Linux with Python 3
- Account
- None needed
Free, open source under the Apache 2.0 licence.
Steps
- 1.Install Python 3 and create a virtual environment.
- 2.Run: pip install opencv-python
- 3.Test it: python -c "import cv2; print(cv2.__version__)"
- Install only one OpenCV package per environment: opencv-python, opencv-contrib-python, or their headless versions. They all use the same cv2 name and clash.
- Use opencv-contrib-python if your course needs the extra modules.
- On servers or Docker without a screen, use opencv-python-headless.
Official download pagepypi.org
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.
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.
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 — deliberately. This course is the classical toolbox that solves most fixed-camera inspection jobs at a fraction of the cost, and it is what the Deep Learning and Machine Vision courses build on. It also teaches you to measure when classical methods fail, so a neural network is a decision, not a reflex.
What are the projects in the Computer Vision with OpenCV course?
A conveyor part counter — detection, tracking, a counting line — debugged on a synthetic belt video with a known count and then run on your own phone video, with misses and double counts reported separately; and a colour-sorting plus 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.
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 factsHide 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.
- ProgrammingKnowledgethe OpenCV Python tutorial for beginners series
- Murtaza's WorkshopLearn OpenCV in 3 hours with three projects
- freeCodeCamp.orgthe OpenCV full course
- SmartVisionLightsa lesson in "Cameras, lenses, lighting and calibration"
- Nicolai Nielsena lesson in "Cameras, lenses, lighting and calibration"
If you are one of these creators and would like a lesson removed or credited differently, write to info@wartens.com.