AI and machine learning · Free
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.
Inside the course
From the lessons
The anatomy of an inspection station
Breen Machine Automation Services LLC
Cameras and sensors
IDS Imaging Development Systems GmbH
Lenses and optics
IDS Imaging Development Systems GmbH
Lighting
Omron Microscan
Triggering, timing and the PLC
IDS Imaging Development Systems GmbH
Classical inspection tools
IDS Imaging Development Systems GmbH
Lesson frames belong to the creators named in the Credits below and are shown from YouTube.
What you will learn
Specify a camera, lens, lighting and trigger from the feature size, field of view and line speed with the arithmetic shown; build a timing budget to the rejector and a PLC handshake with a heartbeat; assemble classical tools with limits and validate them; decide when deep learning is justified and which model type; build a labelled dataset with a written standard; train a YOLO detector, sweep the threshold, choose the operating point with QA, export it and measure latency; and read an integrator's quotation for what it leaves out.
- Turn feature size, field of view and belt speed into pixels, exposure and a lens focal length
- Choose backlight, dark-field, dome or structured light by measured contrast, not opinion
- Build the timing budget to the rejector and the PLC handshake with a heartbeat
- Assemble and validate classical tools — calipers, presence, OCR, codes — with limits and golden samples
- Decide when deep learning is justified, build a labelled dataset with a standard, and train a YOLO detector
- Choose the operating point with QA, export the model and measure latency where it will run
For you
Taking Machine Vision and Quality Inspection from the United States
- Free in the United States, as everywhere, and self-paced: lessons, notes and the final assessment are open at any hour, so your time zone and shift pattern do not matter.
- The optional certificate for learners in the United States is a one-off US$28.99. What you get for it
- Plants across the Americas most often run Allen-Bradley, Siemens and Inductive Automation; each has its own free course to take next.
- See automation and engineering jobs in the United States, and what the industry looks like in Houston, Detroit and Chicago.
- EDWartens also has a regional site for the United States, for classroom training and local support: edwartens.com/us.
The course project · 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.
The course project · about 4 hours
Specify an inspection station and bench-test its lighting
Choose one real product and defect. Write the spec sheet — 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.
Course content
12 modules · 36 lessons · 7h 56m
In order, at whatever pace suits you. Each module ends with a practice task that builds on the last.
- 01The anatomy of an inspection station4 lessons19m
- 02Cameras and sensors4 lessons39m
- 03Lenses and optics2 lessons25m
- 04Lighting5 lessons1h 28m
- 05Triggering, timing and the PLC2 lessons20m
- 06Classical inspection tools2 lessons24m
- 07When to go deep4 lessons7m
- 08Datasets and labelling2 lessons21m
Requirements
- Who it is for
- Intermediate. Needs the Computer Vision with OpenCV course; the Deep Learning course helps for modules 7–10.
- Software
- Google Colab with a GPU runtime and Ultralytics YOLO; a phone camera for the bench test. What to download, and how
- Hardware
- A phone, a torch, a lamp and white paper for the lighting bench test. No industrial camera required.
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.
Machine Vision and Quality Inspection at a glance
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.
All course factsHide course facts
- Price
- Free, for good. No trial, no card. The only paid item is the optional certificate, a small one-off fee.
- 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, 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
A shareable EDWartens certificate
Finish every module and pass the final assessment, and the optional EDWartens certificate is yours. It carries a unique verification code on a public page anyone can check, so it stands up when a recruiter looks it up. See it below.
The course itself stays free whether or not you ever buy one.
Stuck? Ask a practising engineer
A free course usually means a comment section and hope. This one does not. Every module has an Ask-your-trainer panel that reaches the same engineers who teach our paid programme: people who commission panels for a living, not moderators.
Pairs well with
PLC programming · FreeSiemens TIA PortalFrom zero electrical knowledge to a working, simulated S7-1200 program, for nothing.
PLC programming · FreeSiemens TIA Portal in Three HoursThe first three hours of the Siemens TIA Portal course, cut to end on a win: what a PLC is, how it is wired, a project configured in TIA Portal, and your first ladder program running in simulation. Finish it in an evening or two, earn a certificate, and carry straight on into the full course.
PLC programming · FreeTIA Portal: Build a MachineOne machine, start to finish. Take a bottle filling line from a written specification and an I/O list to a structured S7-1200 program with a fill station, a capper, a reject sorter and an operator screen with alarms, then test it against a written record and archive it for hand-over. The lessons are the reference; the machine is yours, and it is what you submit.
Instrumentation · FreeInstrumentation for PLC EngineersThe half of the loop that is not code. Follow one measurement from the transmitter in the field, down the 4-20 mA loop, into the analog card, through NORM_X and SCALE_X into engineering units, out again to a valve, and back to the control room when the reading is wrong.More free courses: Free AI courses for engineers · Free Six Sigma and quality courses
Learning paths with this course
- Industrial AI engineer · 4 coursesAI where the machines are: where it sits beside PLC and SCADA, predictive maintenance on real run-to-failure data, machine vision quality inspection with YOLO, and plant data over Modbus and OPC UA in Python.
Learner reviews
No reviews yet
Reviews here are written only by learners who have finished every module of Machine Vision and Quality Inspection, and they are published exactly as written. Finish the course and yours will be the first.
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?
Train, evaluate, threshold-sweep and export a YOLO defect detector on 640 labelled surface images, ending with the recall-per-defect sentence QA would sign; and specify a complete inspection station — camera, lens, lighting, trigger, timing — for a real product, with the lighting choice bench-tested 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.
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 EDWartens, the training division of Wartens, as a Certificate of Completion for this self-paced course. Sold by Wartens Ltd (England and Wales). 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.
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.