I have 240+ certifications. Want to know how many got me a job? Maybe three.

Don't get me wrong — certifications have value. AWS ML Specialty tells employers you understand the platform. Google Cloud Professional ML Engineer is respected. NVIDIA Deep Learning Institute teaches genuinely useful skills.

But I've sat on hiring panels where candidates lead with "I have 15 certifications" and can't answer "how would you deploy this model to production?"

Here's what actually matters more than certs: GitHub projects that show you can build things end-to-end. Models published on Hugging Face that others can use. Technical blog posts that demonstrate depth of understanding. Open source contributions that show you work well in codebases. Kaggle competitions that prove you can handle messy data.

My recommendation: get one or two high-value certifications (AWS ML Specialty or GCP ML Engineer) to check the box. Then invest the rest of your time in projects.

Certifications open doors. Projects close deals. Put your energy where the leverage is highest.