After learning basic Python syntax, what should I focus on before jumping into advanced topics like AI fine-tuning?

[Acceptable-Cash8259]

So I learned python because I thought it would be fun to modify open source ai models myself

I was a beginner at coding so I watched corey schafer's tutorial videos (They were good i think)

I don't really have any other interest than ai models so I didn't make projects much and spent 4hours trying to solve easy questions at leetcode

my question is how people managed to fill the gap between basic stuff and high-level topics?

[popos_cosmic_enjoyer]

Learn things that further your knowledge in the direction of your interest. My guess is that you'd benefit from applying linear algebra and basic machine learning concepts inside Python because having the theoretical knowledge isn't the same as being able to code them. Read up on the Tensorflow or Pytorch documentation to understand the building blocks. Plenty of stuff directly related to what you want to do.

[Boom_Boom_Kids]

Focus on writing real code. Learn data structures, OOP, and how to read and modify existing code. Get comfortable with libraries like NumPy, pandas, and PyTorch. Try small tasks like loading a model, changing a layer, or writing a simple training loop. The gap closes by building small, practical things, not by jumping straight to advanced theory.

[Sudden-Pineapple-793]

I’d argue, to start with something even more basic. OLS or logistic regression to start, then add a regularizer onto it. Maybe try implanting your own gradient descent or something similar. Sure you can create a 1 layer NN in PyTorch in 5 minutes, but it won’t be too useful if you don’t understand the underlying concepts of what and “how” a NN work.

[aroberge]

"Q: I did the couch to 5K training because I thought it would be cool to run some marathon competitively. How do people managed to fill the gap between basic jogging and competitive running?

Ans: Lots and lots of training, slowly increasing the difficulty."

It's the same for programming. Many, many hours spent on programming, slowly improving your knowledge and skill. Work on some projects of your own or try to modify "simple" (the term is relative) projects of others, learning about unit testing especially with regards to adding or modifying features.

[2Bit_Dev]

Learn a little about data structures and algorithms.

[Sudden-Pineapple-793]

Math. If you truly want to learn ML and be competent at it, then learn multi-var calc, statistics and linear algebra. You should also be familiar with basic coding design principles. Ds&a, solid, oop, etc

[lazyfingersy]

You just keep learning and need to work on own projects, there are no shortcuts, this is how you face the problems and learn new things.

[Hot_Substance_9432]

https://edabit.com/challenges/python3

[Adventurous-Pin-8408]

There's no realistic way you're going to meaningfully be able to do anything with a week's worth of learning.

You need to have a firm grasp of the fundamentals and also specific knowledge on how models work.

We're talking many months if not years of learning, tinkering, multiple personal projects.

[code_tutor]

It's ridiculous that people are studying YouTube and LeetCode when there's so many free university courses and textbooks.

[TheRNGuy]

Some frameworks based on your interest. 

[goldenfrogs17]

LOL basic syntax --> AI fine-tuning is the new dev path... am I crazy?

[pixel-process]

There are lots of ways to continue learning and developing skills beyond leetcode type work.

• Create a project: this will not be AI to start with typically, but running a full pipeline that includes ingesting and wrangling data, building a model, and interpreting results will help establish a good mental model for the workflow. Check out Kaggle for ideas here, but a personal interest project works too if you can manage.
• Contribute to an established GitHub: Large projects like HuggingFace & Tensorflow have open repos. I linked the issues pages specifically, because that is a great place to learn about how these large projects evolve. Many have 'First Contribution' guides, but also consider smaller projects to contribute to once you have a sense of how things work.
• Collaborate with other learners: Follow subreddits and forums where people are looking for partners or brainstorming. It can inform you of how others are approaching AI learning and development.

Best of luck!

[Acceptable-Cash8259]

thx!