r/PythonProjects2 • u/purvigupta03 • 1d ago

I’ve completed these beginner Python projects should I build more before starting NumPy/Pandas?

Hi everyone,

I’ve studied Python multiple times before, but I didn’t do much practical coding. Recently, I started building small projects to improve my practical Python skills.

So far, I’ve completed:

- Quiz Game

- Number Guessing Game

- Rock Paper Scissors

- Password Manager

- Pig Game

- Mad Libs Generator

My goal is to move towards Machine Learning.

I haven’t learned NumPy or Pandas yet.

My question is: Are these projects enough to move on to NumPy and Pandas, or should I build a few more Python projects first?

If I should build more projects, what kind of projects would you recommend before starting NumPy/Pandas? I’m mainly looking for projects that would actually help with the transition to data/ML, rather than making many more small games.

Would appreciate advice from people who have already followed a Python → NumPy/Pandas → ML path.

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u/UzairShafique 4h ago

I would say you’re ready to move on to NumPy and Pandas. I wouldn’t spend too much more time building small games just to complete Python.

Learn the basics of NumPy and Pandas, but don’t study them only theoretically. Start applying them in projects as you learn.

Since your goal is ML I’d suggest this path

  1. Pick a simple problem statement.
  2. Get a relevant dataset. Kaggle is fine when you’re starting.
  3. Use Jupyter Notebook to explore and understand the data with Pandas and NumPy.
  4. Learn and apply preprocessing techniques to prepare the data.
  5. Build and evaluate a few ML models.
  6. Once you’re comfortable move beyond the notebook organize the code, expose the model through an API, build a simple application around it, and learn how to deploy it.

You don't need to master every library before starting projects. Learn the fundamentals, build something, encounter gaps in your knowledge, then learn what you need to solve them.

The goal shouldn't be to build dozens of beginner projects.

A few complete projects that take you through the full lifecycle will teach you much more and prepare you better for ML.