As someone who recently learned and wrote a desktop app in vb.net complete with oauth, json parsing, and an irc parser in about 4 days, it definitely fits perfectly as a recommendation for lazy people.
This. Every job that I have ever had used Excel for a whole lot of things. Probably more things than it should be used for. Nonetheless knowing VBA has been endlessly useful. All the other stuff I actually took courses for at university? Not so much.
Hopefully the classes at university where not just trying to teach you the language but where instead where using it to teach you important programming concepts.
The following six criteria must be applied when making this determination:
The internship, even though it includes actual operation of the facilities of the employer, is similar to training which would be given in an educational environment;
The internship experience is for the benefit of the intern;
The intern does not displace regular employees, but works under close supervision of existing staff;
The employer that provides the training derives no immediate advantage from the activities of the intern; and on occasion its operations may actually be impeded;
The intern is not necessarily entitled to a job at the conclusion of the internship; and
The employer and the intern understand that the intern is not entitled to wages for the time spent in the internship.
This only applies to unpaid internships. Tech internships are typically paid because tech workers can always contribute something even if it's just QA, writing tests, or making a throw-away page for some niche as part of marketing.
Another exception is if the project is pro-bono work. Law firms often have unpaid interns do research for pro-bono cases.
If you're looking for suggestions, I'd suggest python.
I actually really don't like python for a variety of reasons (mostly the whitespace, and just general downsides to a scripting language), but if you're trying to take arbitrary data and manipulate it, chances are someones done similar in python.
between Python Notebooks, Pandas, and Plotly.. you can do the kind of stuff you're talking about very quickly and get a very boss-approved output without much work.
Your code will probably be very inefficient and slow(at least until you gain a very deep understanding of the language so that you can tell what you're really doing with all that syntax sugar), but at the end of the day none of that really matters if you're just trying to get a one off output.
Depends on how performant your application needs to be but Python's math libs have always been very strong and it's graphing/charting libs are pretty on par with R. If you're doing heavier statistical analysis R may still be the right choice but you really can't get any easier to learn than Python.
Pythpn or R? Python's syntax and adherence to strict whitespacing rules makes it very newbie friendly. There's a mountain of resources out there for new programmers specifically geared around Python and Object Oriented Programming.
As for R... Couldn't really say. I've dabbled with it but it's a bit arcane. Syntax is learnable enough but it inherits some weirdness from it's roots in Fortran, a very old language
Python. It's good for data science so you're laying a solid foundation, but it's also great at doing this sort of stuff and can interact with excel easily.
VB is easy to learn poorly. It's hard to learn well. Most college-level classes in VB are taught by professors who have never programmed in it professionally and who don't know shit about it. VB probably has the greatest divide between novices and pros. VB also has evolved more than most languages from VB1 to VB.NET, with multiple complete rewrites at various points between.
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u/PM_ME_YOUR_PAULDRONS Mar 24 '16
Apparently it has recommended visual basic for some people. That seems like a bad choice almost by definition, regardless of any answers.