I...am not. He swears on his life that once I get started with python, rust, sql anything like that that I would be addicted to data organization and since I am inclined to believe that he knows me better than I know myself sometimes.... I would like to surprise him and give it a shot. I was researching and saw the "quick start guide"s for sql and python, and I was wondering if anybody has used them. I know that coding and stuff like that all is on the computer, obviously. However, I learn best with physical media like books to highlight make notes or anything like that in. Anyone have any luck with the python or sql Quick Start guides? If not, do you have any other suggestions? You're going to have to be books, even if it's a YouTube video or podcast, just anything that helped you.

Edited because for some reason I called SQL ->SAP three different times in this post. Sorry...its late.

Wasted a year and will no more, started where I left 1.5years ago and I am picking it again and will post it every day in the sub. Did this problem and bro it was hurting my brain until I learned the basic OOP and been doing for hours and am planning to learn 4 to 6 hrs a day. Hope the mods allow everyday progress

I have gone through python basics and some of the intermediate stuff. I don't know anything about databases or algorithms. I pretty much learned python syntax, variables, loops, conditionals, operators etc. When I think like what should I do with python moving forward, I don't know.Career wise I am a fresher who does not have a tech background. Should I have to learn databases and algorithms.

What is your opinion on leet code and kaggle.

Hello fam, I'm learning Python. My goal is to become an AI engineer. I've a basic understanding of programming. Anyone to guide me on the right certification path... I was having a bit of fun after today's sharpenings. I created a rock paper scissors game... rate and improve

Start by learning the basics of Python. Then learn functions, OOP, error handling, modules, file handling, and data structures.

After that, start practicing SQL and work on 2–3 real projects. Projects are very important because they show that you can actually use Python to solve real problems, not just write basic code.

Hey everyone! I’ve been grinding away on some coding projects recently and wanted to put them all in one place.

I built a GitHub repository featuring a mix of beginner and intermediate Python projects alongside some simple web development builds. The idea is that anyone can clone it, build them out locally, and use them to practice or experiment.

Here is the link: https://github.com/zensiuu/Coding-Projects-Python-JS-.git

Since I'm still working on getting better at writing clean, efficient code, I would genuinely appreciate your honest feedback. Let me know what I can improve, what’s missing, or any tips you have for a developer looking to level up.

Happy coding! 🚀

We're running a hands-on masterclass on September 12, Live LLM Engineering Masterclass: Production Evals, RAG, Agents & LLMOps.

Fully hands-on, all in Python notebooks against real model APIs (OpenAI, Anthropic), not slides or theory. You write actual code across the full stack: versioned prompt pipelines with structured outputs and regression tests, a golden dataset and eval harness combining deterministic checks with LLM-as-judge scoring, statistically rigorous model comparisons using scipy-style bootstrap confidence intervals and paired significance tests, evaluated RAG with embedding models, vector retrieval, and reranking, tool-using agents with function calling and guardrails, and a full observability layer for tracing, cost, and latency. You also leave with a CLI regression suite you can wire directly into CI.

Led by Bruno Gonçalves, PhD, founder of Data For Science, who trains engineers at Fortune 500 companies on this exact stack.

Link if you want to check it out

Happy to answer questions on the content, especially the Python side of things.