# zzsza/Datascience-Interview-Questions

Datascience-Interview-Questions for Korean

Repository: https://github.com/zzsza/Datascience-Interview-Questions
Canonical: https://ross.abutalabs.com/products/datascience-interview-questions
Homepage: https://zzsza.github.io/data/2018/02/17/datascience-interivew-questions/
License: MIT
License Family: permissive
Last push: 2019-11-07T08:27:05+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3120, "days_push": 2491, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1011, forks 235 (observed 2026-08-28T04:03:13.191822+00:00)

## What it is
A Korean-language curated collection of data science interview questions covering statistics, machine learning, deep learning, databases, and data engineering. It is a question-only reference document intended for job seekers, interviewers, and learners, with no answers included.

## Use cases
- prepare for a data scientist job interview
- find interview questions for data analyst candidates
- review statistics and machine learning concepts before an interview
- collect question ideas as an interviewer hiring data engineers
- study data science terminology in Korean

## When to choose
- you are preparing for data science, analyst, or data engineer interviews and prefer Korean-language material
- you need a broad topic checklist of what interviewers may ask
- you want question prompts to structure your own study

## When to avoid
- you need worked answers or explanations - the repo contains questions only
- you need English-language interview prep material
- you need up-to-date content - the document was last substantially updated in 2019

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation
- domain: data-science, machine-learning, tutorials, education
- platform: cross-platform
- tags: interview-questions, korean-language, study-guide, data-engineering, statistics, deep-learning

## Member repositories
- zzsza/Datascience-Interview-Questions (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:13.191822+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:11:53.354188+00:00, confidence not recorded.
  - readme: https://github.com/zzsza/Datascience-Interview-Questions (fetched 2026-08-28T04:03:13.191822+00:00, sha d95cfe0c07f0)
  - homepage: https://zzsza.github.io/data/2018/02/17/datascience-interivew-questions/ (fetched 2026-08-29T13:12:00.019334+00:00, sha 1ffb0dcea49c)
- Data as of 2026-08-30T08:39:29.467469+00:00.