You are an engineer, not a data scientist, and yet you spend hours on your data.
My name is Thibaut, I’ve been an aeronautical engineer for 25 years. I’ve been through this and I’ve found a way out.
Do you recognize yourself?
Your true value lies in your professional expertise.
Your knowledge of the field, the components, and the processes.
But in practice, a good part of your week looks like this:
- Exporting data from software and copying it into Excel
- Cleaning up files that no one has properly documented
- Manually recreating a report you’ve already done 50 times
- Combining sensor data without the right tools
It’s not your job. But you’re the one doing it.
This blog exists to change that.
Concrete methods. Code that works. Real-world results.
No abstract theory. No unnecessary jargon.
Each article starts with a real problem — one you may have right now — and offers a solution you can apply as early as this week.
Python scripts to automate your repetitive tasks.
Methods for analyzing your sensor data without being a data scientist.
Real-world examples drawn from 25 years of field experience in the aerospace industry.
The goal remains the same: to give you back time to do your real job.
Who I am
Thibaut — Aeronautical engineer, not a data guru
25 years in the aerospace industry.
Research projects on predictive maintenance.
Hundreds of hours spent wondering why we were wasting so much time on tasks that could have been automated.
In 2020, I decided to seriously investigate the issue. And what I learned changed the way I work.
That’s what I’m sharing here—no fluff, with actual working code.
Recent Articles
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Solving an Ordinary Differential Equation (ODE) in Python with SciPy — example on an aeronautical ice sensor
In my career as an aeronautical engineer, I never solved a differential equation by hand on a real project. The specialized software — SAMCEF, ABAQUS, NASTRAN — took care of that. We defined the geometry, the materials, the boundary conditions, and the software calculated the natural frequencies and modes. But understanding what the software does…
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Why your industrial data are unusable and how to put them back in order with Python
In an aeronautical predictive maintenance project, the goal was to predict filter clogging based on current consumption measurements. The idea was simple: as the filter becomes clogged, the pump compensates by consuming more power. By monitoring this consumption, it should be possible to anticipate filter replacement before a failure occurs. In theory, it’s elegant. In…
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Why Mechanical Engineers Should Learn Python in 2026 (and Where to Start)
For years, my go-to tool was Excel. Pivot tables, nested formulas, a bit of VBA whenever things got truly repetitive. It was tedious and fragile – one misnamed file or a moved column, and the whole thing would fall apart. But since everyone around me was doing it, I kept at it. In 2020, I…
Do you want to go further?
I’m developing a comprehensive training program on data science applied to industry.
Predictive maintenance, sensor signal analysis, advanced automation.
Code, real-world data, and practical case studies.
Early registrants will benefit from a launch price.