Learning path · Free · No card
AI foundations for engineers
From 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.
Step 1AI and machine learningBeginnerPython 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.
- 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
Step 2AI and machine learningBeginnerGenerative AI and LLM Foundations
What a language model is actually doing when it answers, why it is confidently wrong sometimes, how to call one from Python on a free route, how to run one privately on your own laptop, and how to test one before you trust it with a datasheet. The concept course under the whole AI track.
- Explain in plain words what an LLM does when it answers, and why it hallucinates
- Choose a model for a job: context length, JSON output, local or hosted, licence
- Write a prompt with role, task, context, format and a NOT FOUND rule
Step 3AI and machine learningBeginnerPrompt Engineering for Engineers
Not fifty ChatGPT prompts. The skill of specifying a task to a language model so precisely that the output can be checked — applied to FAT reports, procedures, I/O lists, fault-code guides, code and spreadsheets — and the habit of testing a prompt with a golden set before trusting it.
- Write a five-part prompt with a refusal rule that turns invention into a visible blank
- Fix output format with few-shot examples and get JSON with a schema at temperature 0
- Make calculations checkable with chain of thought, and run the arithmetic as code
Step 4AI and machine learningBeginnerAI Agents and Workflow Automation with n8n
No-code automation with a language model in the loop, for the jobs an engineering office does by hand: triage maintenance tickets, send the 07:00 plant report, log a phone form into a register, watch a mailbox. n8n runs free on a laptop; the AI node points at a free model or a local Ollama. Every write goes through a human approval step.
- Run n8n free on your own laptop and build a form-to-sheet-to-alert workflow
- Read and shape data with expressions, Set, Split Out, Aggregate and Merge
- Make a workflow safe to run unattended: retries, error workflow, idempotent writes
How the path works
Join the path and every course is added to your account at once, each with its own progress, notes, quizzes and final. Take them in the order shown: each assumes the one before. Module quizzes are five plain questions and the final is ten, pass mark 40%, with unlimited retries, so the assessment checks that you followed the lessons rather than testing exam nerves.
Questions
- Is the AI foundations for engineers free?
- Yes. Every course in the path is free in full: lessons, notes, practice tasks and assessments. Joining the path adds all of them to your account in one step. The only paid item is the optional EDWartens Certificate of Completion for each course.
- In what order should I take the courses?
- In the order listed: each course assumes the one before it. Every course keeps its own progress, quizzes and certificate, so you can also take one on its own.
- Do I get one certificate for the whole path?
- Certificates are per course, issued when you pass that course's final assessment and bought only if you want them. Finishing every course in a path gives you one certificate per course.