Best way to start learning Python for data science as a beginner?

Hi everyone,

I’m an Economics student finishing up my MSc, and I want to learn Python, focusing on applying it to data science and economic analysis. I’d like to know where to start. Are there any books or online courses you recommend?

I can dedicate around two hours a day to studying. I’d really appreciate your advice. Thanks!

The best way to learn is by building something you’re excited about. Start with a small project that’s achievable, so you can complete it and feel a sense of accomplishment. Kaggle is a great place to find datasets, though you might want to explore creating something unique rather than just using existing datasets.

You could also try practice exercises instead of passive courses. I created https://bytearena.dev for my partner while she was preparing for Python data science interviews. Exercises force you to practice and engage actively, which is often better than just watching or reading content.

@StarfireSage
Hi! Is this platform free?

Yani said:
@StarfireSage
Hi! Is this platform free?

Yes, it’s free. It doesn’t cost me anything to run right now, and I value feedback more than anything. I might add a paid option in the future, but for now, enjoy it for free!

@StarfireSage
Thank you so much!

@StarfireSage
Out of curiosity, how much does it cost to host this project?

Wei said:
@StarfireSage
Out of curiosity, how much does it cost to host this project?

So far, I haven’t spent anything. It’s hosted on the free tier of Vercel with NextJS for the website and backend. The AI uses ChatGPT, and I’ve only spent $5 so far, which was the initial credit. I also use a free-tier Supabase database for storage. Overall, I estimate it might cost around $0.10 per active user per month if I need to scale.

Here’s a roadmap for you:

  1. Start with the basics: DataCamp or Codecademy has solid Python for Data Science courses.
  2. Check out ‘Python Crash Course’ by Eric Matthes. It’s a great book for beginners.
  3. Learn essential libraries: pandas, numpy, and scikit-learn. These are key for data manipulation and machine learning.
  4. Practice on Kaggle. It’s one of the best platforms for hands-on learning with real-world challenges.

Good luck and happy coding!