AI and machine learning · Free online course
Machine Vision and Quality Inspection
The whole inspection station, not just the model: cameras, lenses, lighting and triggers that make the image; classical tools for what can be measured; deep learning for what can only be shown; datasets and labelling; training, evaluating and exporting a YOLO defect detector; and deploying it beside a PLC that keeps the reject decision.
- 12 modules
- 7h 56m of video
- Intermediate
- English
- ₹0, free
- Lab practice in your browser
₹0Free for good
Worth ₹4,999 by length and depth against classroom training. It has always been free; that is not a former price.
No card. Checkout takes a minute and gives you a receipt.
Overview
About Machine Vision and Quality Inspection
Plan a whole inspection station: cameras, lenses and lighting, classical tools, a YOLO defect detector and a PLC that rejects.
Machine Vision and Quality Inspection is a free, self-paced online course from EDWartens for engineers, developers and students applying AI to real work. It has 12 modules and 7h 56m of video lessons by Breen Machine Automation Services, Cognex, IDS Imaging Development Systems 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
- 7h 56m 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
7h 56m 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
The anatomy of an inspection station
by Breen Machine Automation Services LLC
Cameras and sensors
by IDS Imaging Development Systems GmbH
Lenses and optics
by IDS Imaging Development Systems GmbH
Lighting
by Omron Microscan
Triggering, timing and the PLC
by IDS Imaging Development Systems GmbH
Classical inspection tools
by IDS Imaging Development Systems GmbH
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:
- Specify a camera, lens, lighting and trigger from the arithmetic
- Build a timing budget to the rejector with a PLC handshake
- Decide when deep learning is justified
- Build a labelled dataset with a written standard
- Train a YOLO detector and choose its operating point
How it works
How this course works
Watch the lessons
Short video lessons, one module at a time, at your own pace.
Read the notes
Open the Reading tab for the written notes and diagrams of the module.
Practise in the 3D labOptional
Try the module in the free 3D lab, in your browser.
Check yourself
Answer the questions to see what stuck before you move on.
Final assessment
Pass the final once you have been through the modules.
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
- 36
- Of video
- 7h 56m
- Final questions
- 15
- 01
The anatomy of an inspection station
4 lessons · 19m - 02
Cameras and sensors
4 lessons · 39m - 03
Lenses and optics
2 lessons · 25m - 04
Lighting
5 lessons · 1h 28m - 05
Triggering, timing and the PLC
2 lessons · 20m - 06
Classical inspection tools, with lab practice:
2 lessons · 24m - 07
When to go deep, with lab practice:
4 lessons · 7m - 08
Datasets and labelling
2 lessons · 21m Final assessment · 15 questions, pass mark 60%
3D lab
Practise in the 3D lab
Set up a camera inspection on a moving conveyor: choose the region, the darkness threshold and the blob size to catch bad parts without scrapping good ones.
- Vision inspection on the conveyorAI Workbench, about 25 minOpen in the lab (opens in a new tab): Vision inspection on the conveyor
- Choose the metric and the thresholdAI Workbench, about 25 minOpen in the lab (opens in a new tab): Choose the metric and the threshold
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 5 hours
Train, evaluate and export a YOLO surface-defect detector
640 labelled surface images with scratches, dents and blobs in YOLO format. Train a nano detector on Colab's GPU, validate on the sealed test split, sweep the confidence threshold, pick the operating point QA would sign, export to ONNX and TFLite, and measure latency.
- 8documents in the pack
- 7steps to follow
- 5things to hand in
- 5 hof work, at your pace
Sample document pack, 8 documents, filled in for the scenario
- PlanPlan: defect detector for the panel rework station
- URSRequirements: rework-station defect detector
- DatasheetDataset specification: surface-defects-yolo
- ProcedureProcedure: train, test, sweep and export
- Test reportTest report: training, sealed test, threshold sweep and export
- RegisterModel register
- Risk registerRisk register: from synthetic test set to real panels
- ReportOperating point and QA sign-off
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
Specify an inspection station and bench-test its lighting
Choose one real product and defect. Write the spec sheet. It covers feature size, field of view, resolution, shutter, exposure budget, lens focal length, lighting type and wavelength, trigger, and the timing budget to the rejector. Then bench-test the lighting choice with phone photos and a measured contrast.
- 8documents in the pack
- 6steps to follow
- 4things to hand in
- 4 hof work, at your pace
Sample document pack, 8 documents, filled in for the scenario
- URSUser requirements: scuff and missing-print inspection, folder-gluer line 3
- PlanPlan: specification and lighting bench test
- DatasheetInspection station specification sheet with arithmetic
- I/O handshakeCamera to PLC handshake
- I/O listPLC I/O list for the inspection station
- BOMBudget bill of materials
- Test reportLighting bench test: phone photos and measured contrast
- ReportOne-page station summary and acceptance sentence
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 with a GPU runtime and Ultralytics YOLO; a phone camera for the bench test.
Hardware
A phone, a torch, a lamp and white paper for the lighting bench test. No industrial camera required.
Who it is for
Intermediate. Needs the Computer Vision with OpenCV course; the Deep Learning course helps for modules 7–10.
Video lessons by
- Breen Machine Automation Services
- Cognex
- IDS Imaging Development Systems
- SmartVisionLights
- Advanced illumination
- Omron Microscan
- Ramco Innovations
- Edje Electronics
- TheCodingBug
- Code With Aarohi
- Felipe Tambasco
- DSwithBappy
- MBD Notes
- Pysource
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.
Use a GPU runtime in Colab. A phone camera is enough for the bench test.
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
Ultralytics YOLO
Ultralytics, a Python or npm package
- Runs on
- Windows, macOS and Linux with Python 3.8 or later and PyTorch 1.8 or later
- Account
- None needed
Free under AGPL-3.0 for learning, research and open source projects, but any project using it must also be open source under AGPL-3.0. Commercial or closed-source use, including internal company tools, needs a paid Ultralytics Enterprise licence.
Steps
- 1.Install Python and, if you have an NVIDIA GPU, install PyTorch first from pytorch.org for your CUDA version.
- 2.Run: pip install -U ultralytics
- 3.Test it: yolo predict model=yolo26n.pt
- 4.Find the results in runs/detect/predict.
- The first run downloads the model weights, so you need internet access.
- If you plan to use YOLO at work, read the licence page before you start.
Official download pagedocs.ultralytics.com
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 Machine Vision and Quality Inspection
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$28.99, 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. The specification modules teach the arithmetic you will use to buy one. The bench test uses a phone and a lamp. The detector trains on the track's labelled dataset in Colab.
What do I need before this course?
The Computer Vision with OpenCV course, for the classical tools and the measurement habits. The Deep Learning course helps for the YOLO modules, but the notes are self-contained.
What are the projects in the Machine Vision and Quality Inspection course?
There are two projects. In the first you train, evaluate, threshold-sweep and export a YOLO defect detector on 640 labelled surface images. It ends with the recall-per-defect sentence QA would sign. In the second you specify a complete inspection station for a real product: camera, lens, lighting, trigger and timing. You bench-test the lighting choice on your own photos.
Is the Machine Vision and Quality Inspection 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 Machine Vision and Quality Inspection 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 Machine Vision and Quality Inspection 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 Machine Vision and Quality Inspection course take?
Plan on about 14 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 Machine Vision and Quality Inspection 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, ₹599 including GST for this intermediate 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 ₹4,999.
- Who it is for
- Engineers, developers and students applying AI to real work
- Format
- 12 self-paced modules, 7h 56m of video, written notes, a practice task per module and one final assessment.
- Level
- Intermediate. Intermediate. Needs the Computer Vision with OpenCV course; the Deep Learning course helps for modules 7–10.
- Brand
- Vendor-neutral
- Software
- Google Colab with a GPU runtime and Ultralytics YOLO; a phone camera for the bench test.
- Hardware
- A phone, a torch, a lamp and white paper for the lighting bench test. No industrial camera required.
- Certificate
- Optional EDWartens Certificate of Completion, ₹599 inclusive of GST for learners in India, verifiable by code. Not a vendor credential.
- Video lessons by
- Breen Machine Automation Services, Cognex, IDS Imaging Development Systems, SmartVisionLights, Advanced illumination, Omron Microscan, Ramco Innovations, Edje Electronics, TheCodingBug, Code With Aarohi, Felipe Tambasco, DSwithBappy, MBD Notes, Pysource (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.
- Breen Machine Automation Servicesthe machine vision overview, Cognex camera connection and perfect-image videos
- Cognexthe rule-based, deep-learning and edge-learning explainers
- IDS Imaging Development Systemscamera setup, lenses, triggering, dataset creation and the train-and-deploy tutorials
- SmartVisionLightsthe machine vision lighting basics and selection sessions
- Advanced illuminationdark-field and backlighting education
- Omron Microscanthe introduction to machine vision lighting
- Ramco Innovationsselecting a lens
- Edje Electronicstraining YOLO in Colab and running it on a Raspberry Pi
- TheCodingBugYOLO11 on a custom dataset
- Code With AarohiYOLOv8 on a custom dataset
- Felipe Tambascotraining YOLOv8 on a custom dataset step by step
- DSwithBappydata annotation with Roboflow
- MBD NotesPCB defect detection with YOLO
- Pysourcethe vision inspection and defect detection system builds
If you are one of these creators and would like a lesson removed or credited differently, write to info@wartens.com.