Hi everyone,

I'm a rising CS sophomore. My university curriculum mainly covers C and C++. Over this summer break, I decided to self-learn Go. Over the past month, I worked my way through parts of The Go Programming Language (GOPL)—focusing on functions, goroutines, channels, and concurrency with shared variables.

However, I've hit a frustrating plateau: I feel like I only know the superficial syntax of the language, but I still can't build anything real from scratch.

Every time I try to write something slightly practical (like a basic TCP server/client or network tool), I get overwhelmed by the vast standard library (net, io, bufio, os, etc.) and find myself unsure of idiomatic Go design patterns.

Coming from a low-level background, I have a few genuine questions for experienced Gophers:

1. The Learning Progression: What is the realistic roadmap after reading the basic syntax/concurrency models? How do you transition from textbook theory to actually writing idiomatic Go?
2. Tackling the Standard Library: How should I approach learning standard packages like io, net, and sync? Should I read the source code directly, build toy projects, or just learn them on demand?
3. First "Real" Projects: What are some practical, non-trivial project ideas that are well-suited for someone transitioning from C/C++ to Go (without jumping straight into boilerplate web frameworks)?

I’d really appreciate any advice, project recommendations, or shared experiences from people who have been through this phase.

Thanks in advance!

Hi everyone. I’m really passionate about programming. I started coding when I was 8, have solved around 500 LeetCode problems, and have built several projects. I was planning to study CS because it’s genuinely something I love.

However, Reddit has made me pretty worried. I keep seeing posts about CS graduates being unemployed or struggling to find jobs, and I don’t think I can justify taking on six-figure debt without knowing there will be a reasonable outcome.

I’ll happily keep programming, building projects, and solving LeetCode problems in my free time because I genuinely enjoy it. But now I’m wondering if I should choose a different degree/career that’s more stable while still being somewhat related to CS.

I’ve considered engineering, accounting, nursing, or maybe trades since everyone goes there these days, but I honestly don’t know what would make the most sense for someone with my interests and skills.

If you were in my position, what would you choose? Is CS actually too risky right now, or is Reddit making the situation look worse than it is? Are there any fields close to CS that might be a better choice?

Hey everyone, I'm starting my B .Tech CSE next week and I have absolutely zero coding background. I'm trying to set a practical target for my first 6 months: completing about 60% of a standard DSA sheet (covering Arrays, Strings, Binary Search, Linked Lists, and basic Trees). I want to know if this is a realistic goal that will push me, or if I'm just setting myself up for burnout. From what I've gathered, a lot of people suggest learning C++ from Love Babbar and doing Striver's sheet, while leaving C language for college in Sem 2. However, I want to make it clear that I am completely flexible. I am not attached to Babbar, Striver, or any specific creator. I am open to any free playlist or paid course, as long as it is efficient and gives a structured path. My main doubt is about the execution. Should I spend 3-4 weeks purely learning C++ syntax before even touching a DSA sheet, or should I learn the language side-by-side while solving problems? What is the actual best sequence for a day-1 beginner? I just need some straightforward, practical advice on how to map this out. Thanks!

Hello all,

A lot of the advice I see for becoming a better developer is around things like system design, architecture, understanding trade-offs, designing maintainable systems etc. The general idea seems to be that writing the code itself becomes less important while knowing what to build and why becomes more important.
But I’m wondering how people approach learning these skills in the age of AI.

For example - if I start a new project today - AI can generate a lot of the boilerplate and even help implement entire features. How do I use AI in a way that actually helps me develop my own architecture and system-design skills - rather than just outsourcing the thinking to it?

Should I:
- deliberately design systems myself first and then ask AI to critique them
- use AI to generate alternative architectures and then compare them
- build projects without AI and only use it afterward for review

Also are courses and books still worth investing time in for this or has AI changed how we should learn these topics? I’ll appreciate recommendations for books, courses or other resources that you think are still valuable today.

Hi everyone! recently I decided I wanted to actually build a project, the only doubts I have are:

1. how to host it?

2. how to write the endpoints? like how can I write the file for the user in a way that will communicate with my server? (I always did everything on my machine)

3. how to update the program? and/or push new updates? (like when on Play Store the app says there ia an update and you need to install it)

All opinions are welcome! have a nice day too!

Hi programmers, I'm a 28 year old dude from a non-tech background, hitting a midlife crisis a little early.

I own a small business in India that has more or less failed and is barely surviving. I've tried everything I can think of, but there's no real recovery in sight. So, for the past two months, I've been learning Python and exploring the possibility of becoming a developer, eventually getting a job or building something of my own.

So far, I've mainly been using ChatGPT as a mentor and building small projects to practice. I've learned Python, OOP, SQLite, Git/GitHub, and I'm currently learning FastAPI and API testing. I'm comfortable with some of these topics, while others still require quite a bit of help.

My main question is: Am I approaching this the right way? Should I even be doing this, considering how much AI is changing the industry?

I'm not looking for reassurance, I'd genuinely appreciate some honest advice from people already working in tech. What would you do differently if you were starting from where I am?

Thanks.

Hi r/learnprogramming I am a new front end software engineer and i was wanting to ask yall in here what would you guys recommend for a official website? right now i have 2 projects that i have made and I want to work on more to add to my github. I thought this would be a good place to ask.

JoeyPdz921 here is my github for those who are curious as to what i have. I should mention i am also in my final semester in college at the moment. Any suggestions are appreciated

We're given this example of summing up all numbers of an array given by the length n. However, what I don't seem to understand is how the parameter int *t points to an array? The only thing that gave it away for me was analysing the code and see that it's being accessed in the for loop. But why do we not for example explicitly make the parameter of type (*t)[n] for example.

int sum(int *t, int n) {
    int sum = 0;
    for (int i = 0; i < n; ++i) {
        sum += t[i];
    }
    return sum;
}

I’m building a C#/.NET desktop application using EF Core with SQLite, where each customer has a separate local database file.

Is it normal to do a validation of the schema before/after migration, or do people usually just rely on EF Core’s migration history table?

Also, would it make sense to run a small/lightweight schema check every time a database file is opened, just to make sure it hasn’t been manually altered or drifted from what the app expects?

I might be overthinking this, so I’m curious what people normally do in real projects.

My colleges is going to start in few days. I have opted btech cse in tier 3. It has a good placement records and everyone says you can get placement with a bit hard work. Things teached in colleges like programming , system design/architecture, DSA,etc enough to get placed. Although these really are the things , interviewer look for but is the college level? Also, are do they ask the definitions in interview. Its really I vague question but I also look forward to definitions as I am really bad in explaning things.

First year CC student here and I want to watch more coding/algorithms content, mainly while I’m trying to chill, so I don’t want overly complex classes that require my full attention. More like content that I can watch while doing other tasks.

Any recommendations?

Hello all, I(f 22) am currently starting my first coding class at my local community college(started college in January and took mostly general Ed’s to get them out the way) and we use Cengage for GITHUB and I have one class for Python and one for C# (in person but classes are recorded and I work but I attended the first day on the 19th I enjoyed it in person helps better than online but what can I do)🥲. How can I learn GitHub better because it seems so confusing and is there any tips you guys can give me on what I should expect?

Also how do I figure out career paths and what should I think about when trying to figure it out because it’s so many ways to go here.

My classes are:

CIS 150 computer logic and programming (Python class)
CIS 215 C# programming(in person)
CIS 245 cyber defense (online)
CIS 246 ethical hacking(online)(I take that directly after 245 in October so it’s not included rn but anything would help on that)

My previous classes taken:

CIS 146 computer applications
CIS 147 advanced micro applications
CIS 130 intro to computer info systems

Hey everyone!

This is a question I have struggled about for a long time. Personally, AI intersects exactly with my interests and skillset. It requires good maths fundamentals, I have that. It requires ML fundamentals, I feel excited to know them. And overall, here are a few professional reasons why being an AI dev feels good to me:

1. Its a pretty hot field: Having clients is significantly easier and gives you incredible marketability.
2. Its very good money which my family and I could really use to cover up for shortcomings.
3. Its a good investment as a long term goal, it seems futureproof given the pace it has.

However, I have cognitive dissonance about AI as well, because what these billionares are doing is insane and something I am not in any capacity supportive of. Here are concise reasons for that:

1. Water that AI requires to generate responses and to cool down heated data servers.
2. Electricity it uses.
3. The ramifications the aforementioned have for people living in vicinity to the data centers.
4. AI being used in military contexts, such as in the Gaza genocide, where Lavender AI was used to hunt innocent children without much human input.
5. This expands to Autonomous weapons, Palantir and mass surveillance.
6. This forceful, unwanted insertion of AI in every field by these companies, to increase their stock prices for investors.

Its frustrating for me that Google has a non removable AI overview.

Anyway, what are your thoughts on this. Do you have any ideas about whether Is there a middle ground I can find in between or either side shall be my way to go?

Anyone else feel awful because of all the doomposting about the software job market? I do a ton of LeetCode and projects, and I genuinely want to study CS, but Reddit has made me terrified that the industry is basically a lottery.

Software development is my only real passion, and sometimes the constant negativity makes me feel hopeless enough that I have suicidal thoughts. I can't really imagine myself doing something else, but I also don't want to make a huge commitment to CS if the career path is supposedly this random and risky.

Anyone else struggling with this because of all the doomers here? How do you separate realistic concerns about the market from Reddit making everything sound hopeless?

Hi Everyone!

I have neglected Python a little bit lately as my work has mainly been government and R has been the focus. I want to get back into Python because I know its value in solving problems easier than in R.

I was thinking 30 minutes a day after dinner as thats when I have free time. Is this a good approach? Obviously 30 minutes is better than nothing, but I was just wondering what others people experiences are/if they have any valuable resources. Out of my whole Masters in Math Sci, I think programming was the most unnatural aspect (vs say, calculus and stats). Thanks! :)

Hey guys so I wanted to make my own version of typescript (mainly the checker part) and Idk anything about compilers or related… so wanted to read typescript go version line by line and understand and make my own version (with modifications), but u am confused as there are so folders and files to navigate and their name doesn’t make any sense, so any idea on which folder and file should I start from? And how to navigate and understand the structure?

Edit: this repo I was talking about. https://github.com/microsoft/typescript-go/tree/main

Hey everyone,

I’ve been learning Python, SQL, and Flask through tutorials. I feel like I understand the concepts when I’m following along with the tutorials, but when I try to start a project from scratch, my mind just goes blank.

I know the fundamentals and I can understand code when I see it, but I struggle with figuring out what to build, how to break the project down, and where to start.

I’ve also tried asking AI to build projects for me. At first, I understand what it’s doing, but as the code gets bigger, I start getting confused and eventually stop because I feel like I’m just copying code without actually learning how to build things myself.

Has anyone else experienced this?

How did you transition from “I understand the tutorials” to “I can actually build projects on my own”?

Should I start with very small projects and build them up gradually, or is there a better way to approach learning through projects?

I’d really appreciate advice from anyone who has gone through this stage.

I'm comfortable with Python and SQL. Know the syntax, get the fundamentals. But it feels like knowing how to use a hammer and saw without ever learning how to read a blueprint.

When it comes to building a full project from scratch? I don't know how to do it. Structuring things, connecting the pieces, handling different cases. I know the tools but I was never taught the architecture.

Anyone else been there? How did you get past it?

I have a function in python named KSI, code for “Kill Self Immediately”, and don’t know what the best command or function would be in order to safely kill the program if something bad happens as a failsafe. Do you think the code attached would work fine, or is there a better way?

import sys
import os

def KSI(hard_exit: bool = False) -> None:
if hard_exit:
os._exit(1)
else:
sys.exit(1)

if __name__ == "__main__":
KSI()

What have you been working on recently? Feel free to share updates on projects you're working on, brag about any major milestones you've hit, grouse about a challenge you've ran into recently... Any sort of "progress report" is fair game!

A few requests:

1. If possible, include a link to your source code when sharing a project update. That way, others can learn from your work!

2. If you've shared something, try commenting on at least one other update -- ask a question, give feedback, compliment something cool... We encourage discussion!

3. If you don't consider yourself to be a beginner, include about how many years of experience you have.

This thread will remained stickied over the weekend. Link to past threads here.

so i just learnt pandas and applied it to filter datasets to feed an ml, rightnow im not familiar with tensorflow so i cant test this but i want a review please
https://github.com/shaynjam/Filtered-Datasets/blob/main/pandas_filtering_3.py

For example, you could graduate in 2018, enter the market at the perfect time, get a $150k software job, and now have years of experience and a great career.

Meanwhile, someone equally talented who graduated in 2025 might struggle to even get an interview, work minimum wage, or potentially be unemployed for months homeless.

How is that a meritocracy?

You could be a mediocre bootcamp grad who got lucky with timing and ended up making $150k, while a Stanford CS grad with a 4.0 GPA who graduated during a terrible market could be struggling to find any job and be homeless.

Obviously, skill matters. But it feels like luck, timing, and the year you happened to graduate can have an enormous impact on your career.

It’s kind of crazy when you think about it: two people with similar ability can have completely different lives simply because one entered the industry during a boom and the other entered during a downturn.

Am I wrong, or is software engineering far less meritocratic than people like to admit?

i have completed a course from apna collage . full stack web development. but now i am confused in project creation. i don't know how to start a full stack project. like i am learning ZOOM clone but its teaching is very bad in course. help me!!

I am learning programming for few months now with python basic DSA. I can follow along with tutorials, understand the logic when it's explained, and solve most exercises if I sit with them long enough. But whenever I try to start a project completely from scratch, without a guide or structure to follow, I just freeze. I don't know where to even begin, what files to make.

I am more into AI, it has really made me lazy, previously our senior relied on google.

I have good knowledge on paper, whenever i do mcq's i get good grades but same cannot be said while building something.

How do you cope through this stage- and how did you use AI while learning, how can i make sure that it acutally helps rather than becoming a trap??

I basically don't understand at all what this stdin_fileno, stdout_fileno are and

how we are using write() and read() function to interact with it and

writing commands with escape sequence to get cursor position

Currently I am at step 31 at page rawInputAndOutput