AI for Industrial Automation

No. It is the decision course: what to do first, with what data, on which box, under which rules. The Predictive Maintenance, Machine Vision and Industrial Data courses are where you then build it.

Automation, electrical and instrumentation engineers who are being asked about AI by their managers or customers. They want to answer with a plan rather than a vendor's brochure.

There are two options. One is a readiness audit of one real process. It covers the cost of the problem, a data inventory, a use-case shortlist, a six-week first project, architecture, governance and the ask. The other is a quantified predictive-maintenance business case on the track's datasets, for learners without a plant of their own.

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.

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.

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.

Plan on about 12 hours in all, including the video lessons, notes and practice tasks. It is self-paced, so you work through the thirteen modules at your own speed.

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.

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

The AI for Industrial Automation course has 13 modules. It opens with "Where AI sits in a plant", goes through "The use-case map", "Edge or cloud", "Copilots and agents for the engineering office" and "The AI readiness audit" and ends with "Final assessment". The full list with minutes is under "What you learn" on this page.

After the AI for Industrial Automation course: Place any AI proposal on the control hierarchy and say what the PLC keeps; Match a plant problem to one of seven use cases and name the label it needs; Get data to a model with OPC UA, MQTT and a unified namespace without loading the PLC. These are the practical outcomes the course is written around, and the final assessment of 15 questions checks them.

For the AI for Industrial Automation course, software: None required. Pandas on the track's datasets for the optional business-case project. Hardware: none. The course itself is free.

AI for Industrial Automation is rated intermediate. Intermediate. Best after any PLC or SCADA course in the automation track and the Generative AI foundations; no coding required for most modules. It is written for engineers, developers and students applying AI to real work, and takes about 12.4 hours at your own pace.

Skills from the AI for Industrial Automation course (for example: place any AI proposal on the control hierarchy and say what the PLC keeps) are used in roles such as AI engineer, machine learning engineer, data analyst and automation developer, and in machine learning engineer work. The course gives you practical evidence of the skill; it does not promise a job, and employers decide on experience and interview.