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I think a USDSI certification can make sense as part of a broader strategy, especially if you are new to data science or transitioning from a different field. It gives structure and a credential to show you’ve studied key DS topics. But:
Use it as a supplement — not a replacement for actual DS experience or projects.
Combine certification with hands-on projects, open-source contributions, portfolio building, or practical applications (e.g. Kaggle, personal or open-data projects, real problems).
Treat it as one credential among many — with realistic expectations. It might help you get foot in the door (especially junior roles), but senior-level hiring will still mostly look at what you can do.
If you like — I can pull up 5–10 top independent data-science / machine-learning certifications (including university-backed and vendor-neutral) that tend to have stronger recognition in the U.S. job market than vendor-certs like USDSI, along with pros/cons.
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