Data Science ยท Chapter 43 of 43
Data Science Career
A data scientist's day mixes SQL, Python, statistics, ML and lots of stakeholder communication.
Portfolio + Kaggle + open-source contributions still beat certificates in most hiring processes.
Example 1 (python)
# Build a portfolio: 3 end-to-end projects
# with a README, code, dashboard and writeupPortfolio > certificate.
Example 2 (python)
# Toolbelt: Python, SQL, pandas, scikit-learn, matplotlib, git, DockerCore skills to master.
Key points
- Learn SQL, Python, stats, ML.
- Communication is a real skill.
- Portfolio projects matter.
- Never stop learning โ the field moves fast.
๐ก Note: Great data scientists learn the BUSINESS deeply. The best model tuned to the wrong metric loses to a decent model on the right one.