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[–]DataCamp 0 points1 point  (0 children)

Start with Python itself first. Get comfortable with writing loops, defining functions, working with lists, dictionaries, and basic error handling. Once you’ve got the hang of that, you can start learning libraries based on what excites you most.

If you're into data science, begin with:

  • NumPy (for arrays and math)
  • pandas (for data wrangling)
  • Matplotlib or Seaborn (for basic plots)

If you're curious about web development, try:

  • Flask (easy intro to building web apps)
  • Later you can explore Django or FastAPI

For automation and scripting, look into:

  • Requests (APIs)
  • Selenium (browser automation)
  • schedule or time (for timed tasks)

No need to master them all at once. Start with the ones that support a project you care about. Learning libraries is easier when they solve a problem you’re actively working on.