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bucolic_frolic

(46,736 posts)
Tue Oct 10, 2023, 08:34 PM Oct 2023

I think I need to learn Python, the faster the better

I don't see why many course or certificate rec's limit to 10 hours or so per week. Can't this stuff be accelerated?

Here's a couple ideas, and I'm asking for insights on if these methods might work.

Python As Fast as Possible - Learn Python in ~75 Minutes



How to Learn Python (Step-By-Step) in 2023
https://www.dataquest.io/blog/learn-python-the-right-way/

How to Learn Python FAST with ChatGPT?


Looking to modernize project management skills with a programming language and some data analytics.

Thanks in advance for any input. DU is really a burgeoning think tank!
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I think I need to learn Python, the faster the better (Original Post) bucolic_frolic Oct 2023 OP
Focus on pandas, numpy, scipy Lucky Luciano Oct 2023 #1
Jupyter Notebooks seems a great environment. (This stuff is all free) usonian Oct 2023 #2
Do not forget your IDE Lithos Oct 2023 #3

Lucky Luciano

(11,402 posts)
1. Focus on pandas, numpy, scipy
Tue Oct 10, 2023, 09:14 PM
Oct 2023

Elemnts of statistical learning
Convex optimization thru cvxopt

Kaggle can give you some projects to get started.

usonian

(13,540 posts)
2. Jupyter Notebooks seems a great environment. (This stuff is all free)
Tue Oct 10, 2023, 09:52 PM
Oct 2023
https://jupyter.org/

You can try in your browser?

It’s a notebook. It’s a development environment.


The customary install is to download anaconda (a Python package environment) and use it to install Jupyter or using pip or homebrew. The site above gives instructions for download.

I downloaded the equivalent “carnets” and “carnets plus” for the ipad pro. They are “batteries included” (As is anaconda)

Not only that, but there’s a tutorial and free book (no email needed to download) SKIM!

https://learnpythonwithjupyter.com/

The aim of this book is to teach you coding in Python while developing computational thinking—that is, the way we think when coding. The order of topics is designed to stimulate and strengthen skills such as logic, problem solving, and clean code writing. Python syntax is explained extensively in a simple but precise way, focusing on concepts and vocabulary.

Topics include data types (strings, lists, dictionaries, etc.), if/else constructs, for loops, while loops, functions, modules, and object‐oriented programming. Examples are embedded in narrative to provide context and encourage memorization, and they are enriched with suggestions for code pronunciation. The book includes thirty‐eight chapters, each corresponding to a Jupyter Notebook where you can play with the code explained in the text.

Chapters contain both theoretical exercises, to verify the understanding of concepts, and coding exercises, to learn by doing. Exercise solutions are described in the community forum, where you can ask questions and propose alternative solutions. At the end of each chapter, you will find recaps and “in more depth” sections, with suggestions, tips, and curiosities.

The book is written in a simple and colloquial language while being precise and detailed.
The material of this book was tested and refined over more than a thousand hours of one‐on‐one teaching, with international students of various educational backgrounds.


You can download the notebooks per chapter topic or all at once from that very site.

There’s another tutorial for learning python using Jupyter Notebooks here:
https://www.dataquest.io/blog/jupyter-notebook-tutorial/

This is awesome stuff, from someone who started with punch cards!!
What a bonanza!

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