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EDWartens UK

Free course · AI and machine learning

Python for AI and Engineering Data

Python from zero, taught on the data an engineer actually has: tag lists, 4–20 mA readings, meter logs and motor currents. Variables to Pandas time series in twelve modules, all in a free Google Colab notebook, ending with a real year of plant energy data cleaned and reported.

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Free to learn. Verifiable certificate £19 when you pass the final exam (optional, VAT included).

Level
Beginner
Modules
13
Video
18 hours
Price
Free

Outcome

What you will be able to do

Write Python confidently in Google Colab; use lists, dicts, loops, functions and classes; read and write CSV and JSON; handle errors in real files; do vectorised maths with NumPy; load, clean, resample, group and plot engineering data with Pandas and matplotlib; and deliver a reproducible notebook that turns a messy meter export into a load report.

  • Run Python in Google Colab and read an error message without panic
  • Convert 4–20 mA readings, scale signals and check NAMUR limits in code
  • Turn a vendor I/O list into a clean JSON tag map
  • Read, clean and de-duplicate a data-logger CSV with Pandas
  • Resample 15-minute meter data to daily kWh and monthly maximum demand
  • Plot a week of load with limits and a hour-by-day heatmap, and explain it

Software

Google Colab (free, in the browser). Nothing to install.

Hardware

None. Any laptop or even a phone browser for the lessons; a laptop for the project.

Syllabus

13 modules

Each module has video lessons, notes and a short quiz. The final exam closes the course.

  1. 1Colab, variables, numbers and strings3 lessons
  2. 2Lists, tuples, sets and dictionaries5 lessons
  3. 3Conditions, loops and comprehensions4 lessons
  4. 4Functions and the standard library3 lessons
  5. 5Files: CSV and JSON from loggers and gateways3 lessons
  6. 6Errors, exceptions and debugging2 lessons
  7. 7Classes: objects, methods and attributes3 lessons
  8. 8NumPy: arrays, masks and signals4 lessons
  9. 9Pandas: DataFrames from real files4 lessonsLab
  10. 10Cleaning and grouping engineering data4 lessonsLab
  11. 11Time series: resample, rolling, shift and calendars5 lessons
  12. 12Plotting and the reproducible report4 lessons
  13. 13Final assessment0 lessons

How it works

How this course works

  1. Watch the video lessonsOne module at a time, at your own pace.
  2. Take the module quizA short quiz at the end of each module shows what stuck.
  3. Keep your notesWrite in My notes beside each module and ask the trainer if you are stuck.
  4. Practise in the labOptionalTry a task from the module in the EDWartens Lab, in your browser.
  5. Sit the final examPass it once you have been through the modules.
  6. Certificate, if you want oneOptionalPaid, and only after you pass. Anyone can check it online.

EDWartens Lab

Practise this in the EDWartens Lab

Train a model on plant data, move the decision threshold and weigh the cost of errors in the Lab's AI workbench.

Works alongside Python for AI and Engineering Data. The Lab is ai for industry practice in your browser: no install, no hardware, free to use. Sign in as a learner and it opens with your account.

Open the free lab See the Lab
AI for industry: Build AI models.

Levels to try with this course

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

Why practise in a 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.

Certificate

An optional certificate when you pass

Learning is free. Pass the final exam and you can have a certificate for £19, including VAT, with a number employers can check online. It records that you completed a free online course; it is not a regulated qualification or a CPD certificate.

  • Your name, the course, its study time and your final exam score
  • A unique certificate number and a QR code to its verification page
  • Issued by Wartens Ltd; add it to your LinkedIn profile in one click
  • Pay now or after you pass: it is issued the moment you pass the final

How the certificate works

Sample certificate for Python for AI and Engineering Data

Credits

Who made the lessons

The video lessons belong to their creators. EDWartens wrote the study plan, notes, quizzes and the final exam.

Questions

About this course

I have never programmed. Is this the right place to start?
Yes. It assumes nothing and every example is engineering data, so you always know why a line of code exists. Finish it before Machine Learning with Python.
Do I need to install Python?
No. Everything runs in Google Colab in the browser, which is free and has NumPy, Pandas and matplotlib ready. A Gmail account is all you need.
What is the project?
A year of 15-minute compressor-house energy data, with the gaps, duplicates, offline blocks and spikes a real export has. You clean it, compute daily kWh, maximum demand and shift averages, plot it and write the report. It is marked against a rubric within about a minute of submitting.
Is the 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 do I get?
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?
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 project and the assessments.
How long does the course take?
Plan on about 18 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.

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