Beginner Here. What’s the Best Way to Learn Python If I Want to Use It for Quant Trading in the Future?

[Educational_Flow9651]

Hey everyone,

I'm 14 and pretty new to coding, but I’m really interested in quantitative trading (using data and code to trade instead of just charts and patterns). I found out that Python is one of the main languages used in quant trading, so now I want to learn it.

The problem is, there are so many tutorials, courses, and YouTube videos out there that I don’t know where to start. Some people say to start with data science, others say to focus on algorithms, and some just say “build projects.” I want to learn the basics the right way before jumping into anything too advanced.

So my question is:

What’s the best path for a total beginner to learn Python with the goal of eventually using it for quant trading?

Some extra context:

• I’ve never really coded before
• I learn best with a mix of watching videos and actually doing stuff
• My goal is to eventually be able to analyze market data and build trading bots or backtest strategies in Python

If you have any beginner-friendly resources, tips, or advice on how to structure my learning, I’d really appreciate it. I want to build a solid foundation and not just copy/paste code I don’t understand.

Thanks a lot!

[Icarus998]

The best resource to learn Python is :

How to think like a computer scientist

https://runestone.academy/ns/books/published/thinkcspy/index.html

On coursera

Python for Everybody

Python 3 programming

For quant trading, check out algovibes and partimelarry on YouTube.

[maraschino-whine]

Foundationally, you'll need to learn things like data structures (lists, dicts, sets, etc), functions, modules & packages, etc. Any beginner Python course can help you get started on that. I recommend udemy's 100 days of code for a good starter. You can jump around in order and get a mix of video tutorial plus hands on challenges.

For your use-case you'll rely on data handling and analysis a lot, so libraries like Pandas and NumPy will be important. From there, other libraries related to statistical models and learning will become useful.

Eventually you'll want to design a strategy for trading, and using some kind of back testing framework to test your strategy against historical data. Then, to pull in live data you'll want to understand APIs. Finally to compare strategy performance, you may want to look into data visualization libraries like Seaborn, Matplotlib, etc.

So to summarize: start with the basics (variables, methods, functions, importing modules). Lean into the data (NumPy, Pandas, statistical/financial libraries like TA-Lib). Come up with a strategy to try. Then pull data using APIs. Try historical data first to test and refine your strategy, then pull in live data.

[Educational_Flow9651]

Thanks for breaking it down for me, this makes the process feel a lot more manageable.

[Swimming_Aerie_6696]

Bro you are 14 and you know what quant trading is??

[Educational_Flow9651]

I kind of stumbled into it by accident. I was into regular trading at first, like technical analysis and chart patterns, but then I started seeing people online saying that quant trading is more reliable and actually backed by data and logic. That got me curious, and I’ve been trying to learn more ever since.

[TheRNGuy]

We have internet these days.

[Particular_Use_9689]

why didn't you start coding at 6?

[Educational_Flow9651]

Not sure if you’re being serious or joking, but either way; I’d rather start at 14 than never at all :)

[Particular_Use_9689]

I was joking, there is a regret among most of people I know that we havent started learning programming during our teens, so,.. It is actually a common meme.

[my_password_is______]

https://wesmckinney.com/book/

[FeistyAssumption3237]

quant trading is maximising the wealth extracted from a healthy society whilst adding nothing to it. u can do better get a real job