>get c++ guide in December
>study few pages
>it's not that easy
>too lazy to continue
Start qith Python, then once you have a good grasp on it, move to a better language like C.
>>53713717
not anyone can learn to program. you have to have some amount of brain matter and patience
>>53713717
Who said it was easy
>>53713717
>C++
don't learn to program with this. C++ is a huge mess of a language and is really meant for the niche of projects that are both very large (where you want object-oriented features) and performance-critical (where you need a compiled language with no interpreter/VM or GC, and are willing to trade away dev time for it)
Do what >>53714860 said. Whatever made you interested in programming, there's better first languages. If you just wanna make something useful as quickly as possible, learn Python. If you wanna get down in the weeds and learn how things are laid out in memory at a low level and such, learn C instead of C++.
>>53713717
>get on with c++
>study and learn every in and out about it
>reinvent most stuff
>try to solve math problems or be "innovative" and fail
I just want to die.
>>53718235
What are languages used for cool projects that are not webdev?
Like AI, medical research, engineering, etc.?
>>53718362
AI is kind of a special case with it's own requirements. but other than that a lot of academic "It doesn't need to be optimized or fast, I just need something up and running quickly" projects are in Python now.
>decide to pick c++ for final year project
>no experience with c++ prior
>application is algorithms, audio and graphics
>try to optimize everything
>cannot optimize menus
I don't know, I really like this language, even if I barely have any experience with it.
Switching from bubblesort to quicksort reduced delay from around 240ms per second to 10ms per second.
I love it how you don't need an intepreter like Java does, how you can just carry it around.
I wish I could find a job with c++ for beginners.
>>53718362
well what do you mean? Actual engineering projects (like, building a thing) rarely use low level languages other than for embedded parts. It's a lot of MATLAB tho
Engineering software... well, I think it depends. But it can probably be safely assumed that at least CAD software uses lots of C++, since the whole graphics industry is dependent around that
AI in academics probably some scripting language like the other anon said, production AI (as far as that goes at least) probably some low level language that is good at multithreading
medical research again, anything CT will probably have an involvement with C++, the thing your doctor uses to give you your prescription is probably Java EE or .NET clusterfuck connected to a 300 year old mainframe at some company's campus
>not learning superior C language
>>53718362
>>53713717
lua is a very very good alternative to python
imho lua is the best introduction to imperative/procedural programming like c or java or whatever, and when/if you want to try functional programming it's very simple to translate concepts
main downside of lua in current year is lack of concurrency support, but it has coroutines for basic stuff
from lua i'd move on to c and nim/rust but that's just advice
luajit is excellent also
>>53713717
Oh well, somebody has to say it..
>>53719353
>The big gap between top tier and high tier
Is this legit?
>>53719353
>money tier
>two languages that are saturated with Pajeets and low-paying code monkey jobs
>>53718362
I'm in atmospheric physics and these are the main languages used:
Fortran: because old code is still used (as well as proven to give right numbers and no one can afford re-writing them). It's also quite fast.
IDL: scripting language, handy for plots and array computations. Being faded out slowly in favour of ...
Python: free, available everywhere, great packages for computations and plotting, object oriented (if needed)
C++: larger codes tend to be written in C++ (unless an old prof insists on Fortran). It's mainly a generation thing and as younger researchers come in, they make a claim for C++ instead of Fortran. It's also nicely inter-faceable with Python/Lua etc., so you can create fast code in C++ and call functions from scripting languages.
Matlab: some still prefer this over Python, and most institutes have a license.
R: quite useful for geospatial applications, kriging etc.
Summary here - Python is the future for Earth science data analysis, there's quite a demand from researchers and councils are being asked to provide training.
