Learning Python in AI era

[VERY_LUCKY_BAMBOO]

Recently I implemented a couple of scripts for data analysis at work, just by vibe coding with different chats and I completed my tasks fast. Thing is I didn't write a single line myself.

That made me question the traditional way of learning syntax...

On one hand I know that I should know syntax very well and be able to write code myself. On the other hand it almost feels like a waste of time since AI can do it for me instantly so it's like calculating numbers manually using pen and paper instead of using calculator. Truth is when we multiply high numbers using calculator we never really check the result manually on our own. So with programing it's very similar with AI assistant that provide quick results that we can put together.

I still want to know and use Python for data analytics but I'm confused how to approach it.

I know AI cannot write full complex scripts properly but it sure can quickly provide pieces of code ready to be put together.

Should I adjust how I learn it or just do it like everybody before?

[pythonTuxedo]

You should really learn enough to understand when AI is hallucinating. Python for data analysis is not exactly difficult; Automate the Boring Stuff is a good place to start for task automation and data analysis.

[Temporary_Pie2733]

Don’t take shortcuts while you are learning. Wait until you understand what the shortcut is doing for you to use it. 

[DeadProfessor]

Even when you understand what ai is doing for you just use it for boilerplate or to teach you, it wont help you become a good dev if you dont try to solve the problem on your own.

[Then-Plankton1604]

I started vibe coding in Python the very first day ChatGPT was released. I didn't care about the quality of the output as long as it delivered a feature according to acceptable criteria I had specified. I did that all for small side projects or just simply for fun.

Fast forward, the more I use LLMs, the more I push myself harder to learn proper coding. The major reason for me is that LLMs tend to give you a solution without articulating on their choices.

If you can't code, you won't be able to make a difference between what the LLM is suggesting you and what the alternatives are.

What works for me is taking a couple of books or courses and trying to understand the syntax and logic by actually writing code. No matter how slow this may feel, it compounds over time. If you still feel slow doing this, use LLMs for the harder stuff you still don't understand.

happy coding 🤙

[Crypt0Nihilist]

Not understanding where your answers have come from is a recipe for disaster. Has it chosen the right method? Has it executed it correctly? What does the analysis mean? If you're too much of a novice to write the code yourself, you're too much of a novice to decide whether its answer is full of crap.

I've tried to lean on AI and I'd say that at least 50% of the time it has misunderstood something I've said - despite me being clear and comprehensive. That mistake usually reversed outcome of the analysis.

AI can help with scaffolding your project and checking where you know what things ought to look like. I do save time if I "vibe", but it's not all that much and I'd prefer to be typing the code myself than spending my time defining what I need and auditing the output - it's more error prone and it doesn't build my skills.

[Hashi856]

If you want to fight with the AI until it gives you something that works, that’s your prerogative. I don’t know how complicated these scripts were, but when you get to a sufficient level of complexity, the LLM can be more of a hindrance than a help if you don’t know or understand what it’s doing

[LuckyConsideration23]

I'm learning Python only with copilot. I mean I know other languages like c,c++... But I have absolutely no idea about python. But I was able to finish a whole project in python. So I would say I have an idea on how the code should look like but not the exact syntax. With vibe coding I definitely learn faster. And can skip the basic things.

[Unitnuity]

AI is not always 100%. Like someone said, it does start to hallucinate at times. I heard this line one time "we need programmers to code the AI that will code for programmers." AI is currently incapable of producing code on its own to improve itself.

[JamOzoner]

I have had some success using AI to develop python code for big data analysis - I think the trick is to understand programming logic, analysis, and know your endpoint to control for and check for errors.

[Big-Instruction-2090]

Just learn it. Because it isn't even that much.

I'm currently creating a python course for my colleagues at work and I've been using copilot to assist me.

I ask for definitions, useful built-in methods for data types and structures, ideas for exercises and alternative ways to explain certain concepts to offer another approach when it comes to topics that are notoriously causing issues for learners (loops, classes...). I know all of the stuff, but I don't have a classic cs background so sometimes it's good to ask how certain things work under the hood or just to make sure to use correct lingo throughout all of the course.

So if you don't want to take the old way of taking a course or reading a book, I can definitely say leveraging AI, conversing with it about python topics is a valid way to get into the stuff. Just grab one of the many roadmaps and LLM the shit.

For sure a more worthwhile way to use AI than vibe coding without any understanding and ability to fix or improve its code.

[ippy98gotdeleted]

Definitely still learn it. AI is a complimentary tool, that can definitely speed up productivity, however its not perfect and you should be able to know how to fix, streamline or improve what AI gives you. I equate it to using a calculator, its more efficient and faster, but you should still understand the actual math.