Data
Science.
Statistics, ML, Python notebooks, model deployment. The deep path — for people who want to build models, not just query them. ~9 months to fully hireable.
Google Data Analytics Certificate
Required foundation. SQL, Python intro, Tableau, R basics. Do this before touching ML.
IBM Data Science Professional Certificate
10-course series covering Python, Jupyter, Pandas, Matplotlib, ML with scikit-learn. One of the best free data science programs available.
Statistics for Data Science
Non-negotiable. Probability, hypothesis testing, distributions, regression. StatQuest on YouTube makes it actually understandable.
TensorFlow Developer Certificate
✦ HIREABLE HEREHireable checkpoint. Validates ML engineering skills. Deep learning, CNNs, NLP, time series. Gets you into ML engineer and data scientist roles.
AWS Certified Machine Learning Engineer – Associate
Replaced the retired ML Specialty exam. Covers the full ML pipeline on AWS — data prep, model training, deployment, monitoring. Opens senior DS and ML engineer roles.
3 End-to-End Projects
Data → model → deployment → writeup. One classification, one regression, one NLP or computer vision. Public on GitHub with README.
Aggregated from Indeed, LinkedIn, Glassdoor, Payscale, ZipRecruiter.
Test your knowledge.
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