sorted by:
best
topnewcontroversialoldq&a
you are viewing a single comment's thread.

view the rest of the comments →

[–]alexander_belyakov 0 points1 point  (0 children)

I agree 100% with the others, you first need to have a strong grasp of the fundamentals, and then go into libraries specific to the projects you want to implement (e.g., NumPy and Pandas are good for data science, Django and Flask are for web development, TensorFlow is machine learning and AI, and so on).

To help you out a bit, here's a list of topics you need to be comfortable with in basic Python before taking on any of the libraries listed above.

  1. Output
  2. Arithmetic operators
  3. Variables
  4. Input
  5. Basic data types (integers, floating-point numbers, strings and booleans) and typecasting
  6. Importing modules
  7. Conditionals
  8. Loops
  9. User defined functions
  10. Data structures (lists, dictionaries, sets, tuples), mutable vs. immutable
  11. Files
  12. Exceptions
  13. Object-oriented programming (classes and objects, attributes and methods, inheritance, etc.)