Yesterday I talked about the $30k–$50k gap.

Today I want to show you why it exists.
Because it is not what most engineers think.

Don't forget to check out our YOLO Projects Kickstarter while Early Bird deals are still available.

Back to the gap...
It is not that production CV is impossibly hard.
It is that the curriculum most engineers use was designed for a completely different outcome.

"Demo education" is optimized for one thing:
getting something visible on screen as fast as possible.

• A Colab notebook that runs.
• A bounding box that appears.
• A metric that looks good in a presentation.

That is useful for learning the basics.
The problem is what it leaves out.

It does not teach you how to build a dataset that generalizes to real-world lighting and occlusion.

It does not teach you how to quantize from FP32 to INT8 without destroying precision on edge hardware.

It does not teach you how to select a tracker that handles ID-switching under partial occlusion.

It does not teach you how to retrain when your model starts drifting in the field.

These are not specialist topics.
They are the baseline requirements for every production CV role.

One of our readers summed it up well:

"I went through Udacity, Coursera, Udemy. Your resources were the only ones I found that were practical and ready to use in production."

That is the gap. Senior computer vision engineers average $136,000, while entry-level roles often range from $90,000 to $110,000.

You are not stuck because you lack talent.

You are stuck because the training you received was designed to stop before the hard part starts.

Tuesday I will show you what the other side looks like.

Back the YOLO Kickstarter

Talk soon,
The PyImageSearch Team