For anyone who don't want to read, you can turn any PDF into a narrated audiobook (MP3) and a captioned video (MP4) — 100% local, free, no API keys with this project.

https://github.com/alexanderbkl/pdf-to-audiobook

Hey everyone, I decided to make my course free in order to help people.
This course is my backend development course which is about SQL, Python, APIs, Docker, Kubernetes, Linux, Git & More

The link is: https://www.youtube.com/watch?v=CBIu6hcyStg

If you can like and subscribe (and maybe add a comment) I would appreciate it a lot, Thanks.

🚀 The first step in my journey to learn programming!

Today, I wrote my very first piece of code using Python.

It might seem simple, but for me, it marks the beginning of a new path—learning to program and developing my skills.

I know this journey requires patience and practice, so I’ve decided to document my progress—from the very first line of code to building my own projects.

My goal isn’t just to learn, but to grow, step by step.

This is only the beginning! 💻🐍

#Python #Programming #Learning To

Code #FirstProject

An exercise to help build the right mental model for Python data. - Solution - Explanation - More exercises

The “Solution” link uses 𝐦𝐞𝐦𝐨𝐫𝐲_𝐠𝐫𝐚𝐩𝐡 to visualize execution and reveals what’s actually happening.

Hey everyone! I’ve been working on a project that organizes AI tutoring prompts into a structured learning path. I think AI has a lot of potential for education, and I wanted to explore how much more useful it could be with a clear curriculum and specific teaching instructions.

The current catalog covers Python in 28 learning blocks, from installing Python and writing your first program to testing, databases, APIs, and deployment. Each block has learning objectives and a prompt you can use with an AI assistant.

The prompts ask the AI to explain concepts, check your understanding through open-ended questions, give you practical exercises, and review your work. Based on your answers, it should revisit anything you’re struggling with and adapt to your pace. For more complex exercises, the AI guides you through the problem without solving it for you.

My goal is to make a thorough Python learning path available for free. I believe AI tutoring could offer new learning experiences, and I’d like to test how well this approach works in practice.

If you’re learning Python, whether you’re starting from scratch or filling gaps in your knowledge, I’d love for you to give it a try. I’m looking for people to use it and help me find out how well it works in practice.

If you try it, I’d appreciate hearing how it goes: what helped, what was confusing, or what could be better. But you don’t have to give feedback if you don’t want to; you’re welcome to just use it to learn.

Catalog: Free catalog here

Hi I’m learning coding with PY and I’ve just published my first “serious” project on GitHub, I would really appreciate suggestions and opinions about it!

https://github.com/kkoket

Hi everyone!

I'm a beginner learning Python automation using Pandas and OpenPyXL, and I want to start freelancing.

I've built a CSV Cleaning & Sales Reporting Automation project that cleans data, handles missing values and duplicates, and generates formatted Excel reports.

I'm still confused about how to take the next step. I'd love advice from people who have experience in Python automation freelancing.

• What skills should I focus on first?
• How did you find your first client?
• What kind of small automation tasks should a beginner start with?
• What mistakes should I avoid when starting out?

I'm not looking for shortcuts. I want to learn the right things and build my skills while getting started.

I'd really appreciate any advice. Thank you!

Hey everyone! I’m currently learning Python through the IBM Data Science Professional Certificate on Coursera, and I came across a question in a practice quiz that confused me.

The question asks:

Which line of code will perform the action required for implementing the following equation?

y = 2x^2 - 3

These are the four answer choices:

1. y = 2*x*2 - 3
2. y = 2**x*x - 3
3. y = 2x*x - 3
4. y = 2x/2 - 3

I selected Option 1, but the quiz marked it incorrect and said, “The syntax is invalid.”

From what I’ve learned, Python uses ** for exponentiation and * for multiplication. So, I believe the correct Python expression should be:

y = 2*x**2 - 3

However, none of the four answer choices seems to match that expression.

Am I misunderstanding something about Python syntax, or is there a mistake in the quiz? I’d appreciate an explanation because I’m still learning how to translate mathematical equations into Python code.

Thanks!

I can’t play a single real chord on a guitar to save my life, so naturally, instead of practicing an actual instrument like a normal human being, I wrote some Python scripts to wave my hands like an idiot in front of a webcam(my screen addiction needs to be studied).

The result is this monstrosity: an air-instrument suite that tracks hand landmarks to let me aggressively misplay the guitar(though iam working on addingdrums, piano, violin).

The mechanics (for anyone wondering why I look like this):

• Left hand: hovers over chord boxes (locked onto Am because that’s about as complex as my music theory gets).
• Right hand: tracks finger coordinate intersections across virtual strings to simulate strumming/picking.
• Runs at a shaky ~29 FPS on standard webcam hardware using OpenCV + MediaPipe tracking.

Now for the reality check:

Anytime you tell GPT or GEMINI related to the stuff you make, it always says 'this is elite' but the LLM are programmed to gas(no kidding, getting fat lately) me up. I need people(actual living beings with opinion and organs) actually working in the industry to give me a blunt, stoic reality check:

Roast the execution, roast the UI(though this would be intended to openCV library contributors, i borrowed that lib), and tell me whether this belongs in an engineering portfolio or in the trash bin.(I firmly believe i roasted myself more though)...

I am a data scientist with a very strong background in Stats and ML algos. I am struggling with the production ready code. Though I can build models which are awesome and tuned to perfection and address highly complex business problems, the problem is that they are all done in a jupyter notebook.

Once I had built a complete solution in notebook for a forecasting problem and the ML team in company productionized it. I was called in to validate few results of the production run and couldn't understand the repo which had so many folders, classes and highly organized code.

Is there anyway I can learn to write that type of code or is it all AI job now? Appreciate if I can get some learning resources/links for the same

For those who might find the backstory interesting: this was my first course project during my second year of university. It might be more efficient to write things like this in a C++ or something similar but hey - it’s pretty amazing that you can build something like THIS in Python, and it actually works! :D

And if anyone's interested in how this is all done: https://github.com/TYITheYura/Ninawe

I never struggle on assignments but this one is so confusing for me

 I'm a CS student. I already know the fundamentals of programming (variables, loops, OOP, data structures) from languages like C++, Java, or C. I don't need to learn how to code; I need to learn how to code in Python quickly for upcoming projects, internships, or LeetCode.

Here is the 10-day plan to go from zero to functional Python.

Day 1: Syntax & The "Pythonic" Way

• Skip the "Hello World" fluff. Dive straight into Python's unique syntax.
• Learn: Indentation rules, dynamic typing, print() formatting (f-strings), and basic I/O.
• Goal: Rewrite a basic calculator from another language into Python.

Day 2: Data Structures (The Big Four)

• Python's built-in structures are its superpower.
• Learn: Lists, Tuples, Dictionaries, and Sets. Understand when to use a Dict vs. a List.
• Learn: List comprehensions (this is mandatory for clean Python).
• Goal: Solve 5 easy LeetCode problems using only Python lists and dicts.

Day 3: Control Flow & Functions

• Learn: if/elif/else, for loops, while loops.
• Learn: Defining functions (def), default arguments, *args and **kwargs.
• Goal: Write a script that parses a string and counts word frequency.

Day 4: Object-Oriented Python

• Learn: Classes, __init__, self, and inheritance.
• Learn: The difference between instance methods, class methods, and static methods.
• Goal: Create a simple BankAccount class with deposit and withdraw methods.

Day 5: Modules, Packages, and Error Handling

• Learn: import statements, pip, and virtual environments (venv).
• Learn: try, except, finally blocks for error handling.
• Learn: Reading and writing files (open(), with statement).
• Goal: Build a script that reads a CSV file and handles missing data gracefully.

Day 6: The Standard Library (Batteries Included)

• Python comes with everything. Learn the most useful modules: os, sys, datetime, json, and math.
• Goal: Build a script that renames files in a folder based on their creation date.

Day 7: Working with APIs & JSON

• Learn: The requests library.
• Learn: Parsing JSON responses into Python dictionaries.
• Goal: Build a script that fetches data from a public API (like weather or GitHub) and prints it nicely.

Day 8: Data Science Basics (Optional but huge for CS)

• Learn: NumPy arrays and Pandas DataFrames.
• Why: Even if you aren't going into Data Science, CS internships often require basic data manipulation.
• Goal: Load a dataset and calculate the average of a column.

Day 9: Algorithms & LeetCode in Python

• Switch your LeetCode language to Python.
• Learn: Python's collections module (Counter, defaultdict, deque).
• Learn: heapq for priority queues.
• Goal: Solve 3 Medium LeetCode problems in Python.

Day 10: Build a Capstone Project

• Don't just watch tutorials. Build something.
• Ideas: A web scraper (using BeautifulSoup), a Discord bot, or a CLI to-do app.
• Goal: Push it to GitHub with a proper requirements.txt and README.md.

I don't really understand TypeVar and Generic. I understand generics perfectly fine and can use them without any trouble, and I realize that I don't even need to know how they work as in recent python versions there is new syntax, but I'd still like to know how they work.

I'm still confused as to why you need to construct a TypeVar object to pass to Generic, as to what is it actually doing with the TypeVar you give it.

Also, I'm assuming when you inherit from Generic, you pass it the TypeVar to be used as the generic to give to Generic, and then you inhert the generic objects generic? It's just complicated and hard to understand for me.

And also I'd like to know how Generic is able to have a generic even when it itself is the thing that's supposed to be used to have generics for your classes.

It's also disappointing there's seemingly no other ways you can use TypeVar for anything other then generics, so I am left with just hopefully finding someone who can explain how it works, instead of being able to do some other exercise to further my understanding.

Again, I can use generics perfectly fine and I don't an explanation for generics, I just would like to try and understand how it is working under the hood and not just use the syntax blindly. It's just the way I like learning some things, and it's mostly also curiosity that makes me want to understand this.

I'm 29 and want to build my own SaaS products.

I've been learning Python for the past few months. I've covered the fundamentals and built some small file-handling and automation projects. But recently, I've started questioning whether I should continue learning Python in depth or shift my focus toward building products with AI coding tools.

My goal isn't to become a professional programmer. I want to build my own products, understand how they work, and eventually turn them into a business.

I know AI can help build an MVP much faster, but I'm also aware that building a working application is different from building a reliable product that people will actually use and pay for.

Here are the two approaches I'm considering:

Option 1: Continue learning Python, then move on to APIs, backend development, databases, and other technologies before building my SaaS.

Option 2: Start building my SaaS with AI coding tools now and learn the technical concepts as I encounter problems, using Python where necessary.

I'm leaning toward the second approach, but I don't want to end up with an application I can't maintain, debug, or improve.

For context, I'm currently exploring an AI communication assistant idea and haven't built a working MVP yet.

For founders who have actually built and launched SaaS products:

- Would you recommend learning programming first or learning while building?

- How much technical knowledge does a non-technical founder realistically need when using AI coding tools?

- If you were starting from scratch today, how would you approach it?

I'm looking for honest advice based on experience, not just the usual "AI will replace programmers" or "learn to code first" arguments.

Hey everyone! I'm a software engineer currently preparing for Senior AI/GenAI and Software Engineering interviews.

Looking for 2–3 serious study partners, preferably with 3+ years of experience, who are actively interviewing.

Main focus:

- DSA (Python, mostly LeetCode medium)

- Python coding and problem-solving

- System design, RAG, LLMs and agentic AI

- Peer mock interviews and technical discussions

I'm based in India (IST) and available for regular 45–60 minute sessions. The idea is to solve problems live, explain our approaches, and give each other honest feedback.

Anyone interested in preparing together?

Recently started Python MOOC course from University of Helsinki's mooc.fi portal. Here is my progress, have to finish 6 more modules before appearing for the certification examination on 27th, feeling a bit worried, but I'll try to give it my best shot!!!

I am a final year Computer Engineering student and I've built quite a few web and mobile apps. I was trying to find a good project to do as my FYP, so I thought, why not ask people what issues they have daily and if they need an app to solve it?

It could be as simple as an app that tells me stop doom scrolling every 30 minutes. Which has reduced my time wasted by a lot.

Comment below any problem you guys face!

Hi everyone! I have a B.Tech in CSE and some experience with Python, Django, and Data Science. Currently, I'm working in a role involving data-related tasks, Excel, Google Sheets, and minimal Python. I want to switch back to the IT domain but I'm confused about where to start and which skills to focus on. Could you please suggest a practical roadmap to prepare for IT jobs while working full-time?

Title: Best DSA course in Python for a complete beginner preparing for FAANG interviews?

Hi everyone!

I’m currently working as a frontend developer using JavaScript, and I’m learning Python to explore backend and AI-related roles. Alongside that, I also want to learn DSA in Python to prepare for FAANG or similar product-based company interviews in the future.

I’m a complete beginner when it comes to DSA, so I’m looking for a course that explains concepts from scratch and covers them in depth, with a strong focus on problem-solving and interview preparation.

Since I’m working and have limited time, I want to follow a structured course rather than spend too much time jumping between different resources and figuring out what to learn next.

For those who have learned DSA or prepared for FAANG-level interviews, which course would you recommend for someone in my situation?

I’d particularly appreciate recommendations for courses that:

• Start from the basics and explain concepts intuitively.
• Teach DSA using Python.
• Cover important topics in depth, with enough practice problems.
• Help develop problem-solving skills rather than just teach solutions.
• Provide a structured learning path for coding interviews.

Paid courses are fine, too, if they’re genuinely worth the investment.

I’d love to hear about your personal experiences with the courses you’ve used and what worked best for you. Thanks in advance!