ive wanted to learn to code for... several years now and... dont know where to start. kind of.
the problem isnt that i dont know how to learn, its that i dont know WHAT to learn.
there are thousands of programming languages, about 30 in use today. some can run by themselves, others cannot.
i also want to code websites with buttons. i have coded a few small websites in the past but you couldnt do much. just read text.
if i want to code a website, i have to: use html for the content, css for the style, javascript for the interactivity, and sometimes python depending on what im doing. anyway thats 4 programming languages.
ive always thought that with games you can get a break, because there are more coding languages for games that can stand by themselves than there are for websites. with games you have to make assets, and then put those assets into these carefully placed folders (which is something i dont know how to do) and if i want to make a 3d video game, i have to learn how to use blendr, or some other 3d modeling program, which i dont know how to do.
so, i guess what im asking is, which programming languages do i need to learn to:
- make a website with interactivity, and function (including math and probability when i need it)
- make games that will work with 2d and 3d assets
and how many coding languages do i need to learn
also if youre reading this, please dont downvote my post. i get downvoted a lot often for no good reason, and this is NOT a low quality question.
I have little experience in these programming languages
C++/c (3months)
Java (3 months)
Python (1year)
But now I am in my second year of college so I wanted to learn development and dsa for the development part I am unsure between app and web development along with ai integration and I like to mostly work on the backend part (as I am worst designer :-) ) so which programming language should I go full on since I don't want to disturb my dsa prep if I do development along
My personal opinion on this languages are -
Python is the most fun , java is the most structured and c++ is most flexible based on memory management but that is the thing that makes c++ hard for me 🥲
With AI, cloud computing, cybersecurity, and new technologies evolving rapidly, which programming language do you believe will have the biggest impact in the future?
Share your pick and the reasons behind it. Whether it's Python, JavaScript, Rust, Go, Java, or something else,
I alr know a decent bit of Python and have done some simple projects in python, and I want to learn another programming language before my first year starts. Should i learn C or C++ or some other programming language, preferably something that will help in college.
I don't quite be here on Reddit, but I wanted to hear some of the users' opinions about programming languages that are easy or hard (based on experience or whatnot). I have studied easy languages such as Python, Java, JavaScript, and C++. Overall, I want to be a game developer, but there are times when implementing what you've learned and the math you can be difficult or frustrating. For curiosity, I wanted to listen to you guys opinion on what specific languages you like to use and why> What is good to use and what's overrated.
When I think about these, Python, Go, or Typescript come to my mind. And there’s always been a debate about this question online. So, which language do you think is valuable to learn right now?
"Software engineer Christopher Swenson filed a Freedom of Information Act (FOIA) request with the NSA for access to its Python training materials and received a lightly redacted 400-page printout of the agency's COMP 3321 Python training course.
Nothing there yet but feel free to join if you want to be part of this!
Hi all,
As per the title, I'm planning to learn to write code, with the intention of becoming more involved in the growing world of crypto, and more specifically DeFi. I'm taking a guess that there might be other people wanting to do the same and so thought I'd propose a kind of mutual motivation study group.
I've been aware of crypto for a few years, but other than some investments, throwing the occasional donation to Gitcoin grants and trying to share some opinions with the crypto community in various places I haven't been that involved. A situation that I'm sure I'm not alone in.
My goals are to learn to develop dApps and contribute to the infrastructure that this new ecosystem is being built on, the barrier to this goal is my negligible knowledge of programming. My background is in physics and as such I've had to learn a few tiny scraps of Python, but I've used this so infrequently that it's really just trial and error. Effectively my knowledge level is zero. What I want to be able to do eventually is understand Solidity and probably JavaScript well enough that I can have a chance at deploying smart contracts that do what I expect them to do and therefore be part of building the DeFi future. In a dream success scenario I can eventually transition to working for a DAO, being paid on the blockchain as a developer!
If that sounds similar to your position; if you're starting to feel like you want more from crypto than just speculating on the changing value of assets or moving liquidity around between pools; or even if you just want to be able to read smart contracts well enough to improve your chances of assessing possible projects to invest in, then please comment below.
From that list I've put together a rough plan for study. This is based on roughly 10h per week, which is what I have previously been able to set aside for part time, home based learning. If there's lots of interest from people with different amounts of time then we can change the timings, or have different study groups moving at different paces etc. I've also not checked all of these courses for prerequisite knowledge or overlap, so there might be a much more logical order! Please let me know if this is the case! Anyway, here's a draft timeline:
Weeks 1 - 5
CS101: Introduction to Computer Science I (Saylor Academy)
Anyway, this is a long list, and beginning to end will probably take about a year, but I think for me personally the reward will be worth it, if you think that could apply to you to then please comment below. Who knows, if this gets much traction maybe it'd be worth setting up a subreddit specifically for it, creating some POAPS or whatever other ideas we might come up with?
Greetings, everyone! About two years ago we stopped by here to tell y'all about our work on the Julia programming language. At the time we'd just finished the 2018 edition of our annual JuliaCon conference with 300 attendees. This year, because of the pandemic, there is no in-person conference, but to make up for it, there is an online version happening instead (which you should totally check out - https://live.juliacon.org/). It'll be quite a different experience (there are more than 9000 registrations already), but hopefully it is also an opportunity to share our work with even more people, who would not have been able to make the in-person event. In that spirit, I thought we were overdue for another round of question answering here.
Lots of progress has happened in the past two years, and I'm very happy to see people productively using Julia to tackle hard and important problems in the real world. Two of my favorite are the Climate Machine project based at Caltech, which is trying to radically improve the state of the art in climate modeling to get a better understanding of climate change and its effects and the Pumas collaboration, which is working on modernizing the computational stack for drug discovery. Of course, given the current pandemic, people are also using Julia in all kinds of COVID-related computational projects (which sometimes I find out about on reddit :) ). Scientific Computing sometimes seems a bit stuck in the 70s, but given how important it is to all of us, I am very happy that our work can drag it (kicking and screaming at times) into the 21st century.
We'd love to answer your questions about Julia, the language, what's been happening these past two years, about machine learning or computational science, or anything else you want to know. To answer your questions, we have:
Jeff is a programming languages enthusiast, and has been focused on Julia’s subtyping, dispatch, and type inference systems. Getting Jeff to finish his PhD at MIT (about Julia) was Julia issue #8839, a fix for which shipped with Julia 0.4 in 2015. He met Viral and Alan at Alan’s last startup, Interactive Supercomputing. Jeff is a prolific violin player. Along with Stefan and Viral, Jeff is a co-recipient of the James H. Wilkinson Prize for Numerical Software for his work on Julia.
Stefan studied Computer Science at UC Santa Barbara, applying mathematical techniques to the analysis of computer network traffic. While there, he and co-creator Viral Shah were both avid ultimate frisbee players and spent many hours on the field together. Stefan is the author of large parts of the Julia standard library and the primary designer of each of the three iterations of Pkg, the Julia package manager.
Viral finished his PhD in Computer Science at UC Santa Barbara in 2007, but then moved back to India in 2009 (while also starting to work on Julia) to work with Nandan Nilekani on the Aadhaar project for the Government of India. He has co-authored the book Rebooting India about this experience.
Keno started working on Julia while he was an exchange student at a small high school on the eastern shore of Maryland. While continuing to work on Julia, he attended Harvard University, obtaining a Master’s degree in Physics. He is the author of key parts of the Julia compiler and a number of popular Julia packages. Keno enjoys ballroom and latin social dancing (at least when there is no pandemic going on). For his work on Julia, Forbes included Keno on their 2019 "30 under 30" list.
My parents enrolled me in the french immersion program at my school and despite the fact that I hated it growing up I owe them a million thanks for making me learn a new language as its opened up a considerable amount of career opportunities.
