Data scientists vs. developers: very (very!) different professions

on YouTube ↗46m

" summary

Compares data scientists and software developers by naming differences in tools, deliverables and workflows—despite both writing code—and warns against blindly copying developer tooling and best practices to data science. Describes challenges encountered when implementing and using “coder-oriented” features in a data science platform, highlighting what makes data scientists a distinct type of coder.

AI-written summary · about

" chapters (11)

1. 0:00Introduction
2. 3:29The Ideal Data Scientist?
3. 4:48In Practice
4. 5:59Development Cycle
5. 14:39Tools & Project Structure
6. 19:39Version Control
7. 23:25Testing
8. 30:38Debugging & monitoring
9. 37:03Common Battles
10. 39:23Final Words
11. 42:03DEVOX

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