I tried 30+ Python courses for Data Engineers.

When I decided to learn data engineering, I did what everyone does:

1. Started with random YouTube tutorials

2. Bought a bunch of Udemy courses

3. Jumped around without a clear path

And six months later… I still couldn't build a real pipeline.

Here's what I learned the hard way:

→ Most Python courses teach you syntax, not systems.

I didn't need another "intro to Python" course. I needed to know how Python fits into real ETL workflows.

I needed:

• SQL + Python integration
• How to structure transformation logic
• Real pipeline patterns companies actually use

Not abstract exercises. Not toy projects.

So I tested everything, figured out what actually works, and in my latest video I break down the 4 Python courses that take you from beginner to job-ready.

Watch it here → https://youtu.be/0vLsTOb5DH4 

And if you want the fastest path?

👉 DataCamp's Data Engineer in Python is where you start. It's hands-on, project-based, and teaches you Python in the context of real pipelines: https://datacamp.pxf.io/55eLnD

It's the roadmap I wish I had—Python, SQL, Spark, and ETL workflows in the right order instead of jumping between random tutorials.

Luke