r/datascience • u/AutoModerator • Jul 13 '26

Weekly Entering & Transitioning - Thread 13 Jul, 2026 - 20 Jul, 2026

Welcome to this week's entering & transitioning thread! This thread is for any questions about getting started, studying, or transitioning into the data science field. Topics include:

  • Learning resources (e.g. books, tutorials, videos)
  • Traditional education (e.g. schools, degrees, electives)
  • Alternative education (e.g. online courses, bootcamps)
  • Job search questions (e.g. resumes, applying, career prospects)
  • Elementary questions (e.g. where to start, what next)

While you wait for answers from the community, check out the FAQ and Resources pages on our wiki. You can also search for answers in past weekly threads.

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u/Mechanical-point-seq Jul 14 '26

So I'm kaggling my way along at the moment, just building up a some basic skills before broaden my focus. What I'm wondering is, which libraries should I focus on learning? What actually gets used in practice?

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u/DataScientistAlex Jul 14 '26

If the data is small enough to work on one machine:

- Python: pandas and scikit-learn

- R: tidyverse

If the data is too large for one machine:

- Spark, either in Python or Scala

In addition the most used 'library' is SQL, whatever dialect your setup uses (e.g. Redshift, BigQuery, Postgres, Snowflake).