AI and machine learning · Free · ₹0
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.
Inside the course
From the lessons
Colab, variables, numbers and strings
Corey Schafer
Conditions, loops and comprehensions
Corey Schafer
Files: CSV and JSON from loggers and gateways
Corey Schafer
Classes: objects, methods and attributes
Corey Schafer
Pandas: DataFrames from real files
codebasics
Time series: resample, rolling, shift and calendars
codebasics
Lesson frames belong to the creators named in the Credits below and are shown from YouTube.
What you will learn
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
Course content
13 modules · 43 lessons · 12h 19m
In order, at whatever pace suits you. Each module ends with a practice task that builds on the last, and a short quiz.
- 01Colab, variables, numbers and strings4 lessons1h 17m
- 02Lists, tuples, sets and dictionaries3 lessons50m
- 03Conditions, loops and comprehensions4 lessons52m
- 04Functions and the standard library3 lessons1h 12m
- 05Files: CSV and JSON from loggers and gateways3 lessons1h 1m
- 06Errors, exceptions and debugging2 lessons25m
- 07Classes: objects, methods and attributes3 lessons47m
- 08NumPy: arrays, masks and signals4 lessons1h 35m
- 09Pandas: DataFrames from real files4 lessons1h 5m
- 10Cleaning and grouping engineering data4 lessons52m
- 11Time series: resample, rolling, shift and calendars5 lessons54m
- 12Plotting and the reproducible report4 lessons1h 30m
- 13Final assessment0 lessons0m
Requirements
- Who it is for
- Absolute beginner. No programming experience assumed; any electrical or automation background helps you see the point of every example.
- 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.
Python for AI and Engineering Data at a glance
Python for AI and Engineering Data is a free, self-paced online ai and machine learning course from EDWartens India with 13 modules, 12h 19m of video lessons, written notes, practice tasks and assessments, and an optional verifiable certificate.
- Price
- ₹0, free for good. No trial, no card. Comparable classroom training of this length costs about ₹5,999.
- Format
- 13 self-paced modules, 12h 19m of video, written notes, a quiz per module and a final assessment.
- Level
- Beginner. Absolute beginner. No programming experience assumed; any electrical or automation background helps you see the point of every example.
- Brand
- Vendor-neutral
- 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.
- Certificate
- Optional EDWartens Certificate of Completion, verifiable by code. Not a vendor credential.
- Video lessons by
- Corey Schafer, codebasics, freeCodeCamp.org (independent creators, credited below)
- Language
- English
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.
- Add it to your LinkedIn profile in one click
- Link it from a CV or portfolio, the URL is permanent
- Publicly verifiable by code, not a PDF anyone can edit
- Issued by EDWartens India, the training centre itself
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.
- Questions answered in the context of the module you are on
- The same engineers who teach the AEP programme
- Career tools, CV help and public job listings included
- Your progress and notes stay in your account for good
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Process control · FreeSiemens TIA Portal PID Compact and Analog ProcessingClosed-loop control the way it is done on an S7-1200 or S7-1500: analog in, NORM_X and SCALE_X, PID_Compact configured, tuned and wired to an HMI, analog or PWM out, proved on a free tank simulation.Learning paths with this course
- AI foundations for engineers · 4 coursesFrom zero code to a working AI assistant: Python on engineering data, how large language models actually work, prompting for engineering documents, and AI agents and workflow automation with n8n.
Learner reviews
No reviews yet
Reviews here are written only by learners who have finished every module of Python for AI and Engineering Data, and they are published exactly as written. Finish the course and yours will be the first.
Common questions
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 submitted a project and passed the final assessment, 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.
What you walk away with
Your certificate for Python for AI and Engineering Data
Finish the course, pass the final, and this is the document with your name on it.
Verifiable by anyone
A unique certificate number and a public verification page. A recruiter checks it in ten seconds.
Adds to LinkedIn in one click
Issuer, credential ID and URL prefilled, with 5 matching skills to pin to your profile.
QR code on the certificate
Scans straight to the verification page, so a printed copy proves itself.
Names what you can do
Lists the topics covered, from python syntax, data types, control flow and functions to google colab, virtual environments and reproducible notebooks.
A permanent link
Put it on a CV, a portfolio or an application. The URL never changes.
Earned, not attended
Issued only after every module and a final assessment at 70%, with three attempts. That is why it stands up.
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, ₹459, GST included, with a receipt.
Issued by EDWartens India (Wartens Automation Private Limited) as a Certificate of Completion for this self-paced course. 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.
- Corey Schaferthe Python tutorials for beginners and the matplotlib series
- codebasicsthe Pandas and NumPy tutorials
- freeCodeCamp.orgthe NumPy course for beginners
If you are one of these creators and would like a lesson removed or credited differently, write to info@wartens.com.