I just finished Python Programming for Economic and Finance.
I’ve enjoyed it a lot, but now, as my main goal is to do Data Analysis ( I’m in my last year of a degree in Economics) I want to start the QuantEcon DataScience, and continue after with the Quantitive Economics lectures, but I see that it “starts again”, showing the basics of Python, Pandas, functions, … and other content already covered in Py. Prog. for Ec. and Financ., but with some small changes.
From where should I start the Data Science lecture? Should I go directly to Applications? Or the lectures of Scientific Computing and Pandas cover some stuff needed that doesn’t appear in the lecture I’ve already done.
Thank you very much!
Hi @Javier , just wanted to say that I’m glad you enjoyed the PP for EF series of lectures and all feedback is appreciated. We will be working through it in the next few months to add GPU support.
The Data Science lectures are managed by @jlperla and @cc7768 so I will let them direct you further.
Thank you very much, it’s amazing how well done is QuantEcon.
It’s an honor to talk with you.
And I’m looking forward to @jlperla and @cc7768 response.
Thank you all again for this amazing place.
I think it depends on your background. These lectures were written for people with very little programming experience so I would go through to see what topics you find interesting.
Agree with what Jesse says.
I’d skim through most of the intro lectures and scientific computing (I’m guessing you’re pretty familiar with this material) but, unless you’ve had other experience using pandas (beyond the other QE lectures), then I suspect there is a lot to learn in the pandas section. There is lots of great stuff in the tools/applications section as well.
Don’t hesitate to drop questions in the discourse (make sure to tag us)!
@jlperla @cc7768 Got it, thank you so much for the responses.
Have a nice day and thank you for this amazing place!