I'm Starting in DataScience – Where to Begin?
summary
A two‑year self‑study journey into Data Science, listing exact beginner courses (Andrew Ng style MOOCs), participating in Kaggle contests, and showing early failed projects (bitcoin prediction) alongside a simple baseline that achieved 30% versus a 45% winning score. Covers tools and workflow: pandas and Jupyter for data work, then scikit‑learn and TensorFlow for modeling; outlines time commitment (~10 hours/week for a 3‑month curriculum), points to concrete resources and community help, and reports a practical outcome — a predictive‑maintenance role at a major Toulouse industrial company.
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chapters (12)
- 0:00Introduction
- 3:00Impostor syndrome
- 5:36First steps
- 7:20Theory and resources
- 11:12Kaggle competitions
- 12:36Python tools
- 15:44Data science careers
- 18:55Learning resources
- 22:45Career change advice
- 26:41Professional reconversion
- 33:03Action plan
- 37:17Conclusion
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