Hi there guys. My university has just started offering free coursera.org online courses, giving us the opportunity to convert those in valid credits.
I'm currently studying management with a glimpse of human resources organization and sociology. I hold a sociology bachelor's degree, I attended a bunch of summer schools on social science research techniques and methodology, and I'm very curious. I love to explore and practice stuff.
I'm very interested in strengthening my data analysis skills, so my choice is between studying Excel for Business or learning Python basics. I have a basic knowledge of Excel and zero about Python or programming in general. I have a certain grasp on calculus and statistics, even if my university courses aren't heavily focused on these subjects.
Excel is a very common tool, universally present in every company, in every sector. Also easier to learn [just maybe?]. The online course is 4 weeks long.
Python is more complete but also complex. It could also give me the chance to access larger sets of data and automate stuff. The online course is 7 weeks long.
I don't know what position I'll be looking for after university, but I aim to have as many as possible job opportunities. My fear is here in Italy few employers know about Python and how to use that in business.
But somehow, my gut says that Python could be the right choice. What do you guys think?
I’m sure your specific goals determine the best answer, but for myself it was best to begin with excel and learn the fundamentals of data and its modeling capabilities [it’s the same as Power Bi, so it translates well for other uses]. Then move on to Python for more advanced usage.
There are plenty of great free resources for excel. I eventually spent like $10 on a few Udemy courses and made the learning experience easier and more convenient. Worth it IMO.
I use R, not Python, but my comment applies regardless. Everyone has made the point about larger data, so I'll go a different direction.
Reproducibility. This is incredibly important in 1] not wasting your time and 2] consistency. If you made some transformations to a dataset in Excel and I gave you an updated version of that same dataset a year later, could you recreate those transformations? Even if you could remember exactly what you did the first time, you'd be wasting your time redoing what you've already done.
When I get a dataset to clean, I write a .R script file of all my transformations. Everything I've done to change it is all right there in one place with comments explaining why I did those things. I frequently get upated data and have to re-run the scripts. Over the course of a project I might re-run the same data transformations dozens upon dozens of times.
Using a language like R or Python saves a great amount of time and ensures I don't mess anything up. With R, I'd be done re-running those transformations while you're still trying to remember which Excel command you started with.
Hi there guys. My university has just started offering free coursera.org online courses, giving us the opportunity to convert those in valid credits.
I'm currently studying management with a glimpse of human resources organization and sociology. I hold a sociology bachelor's degree, I attended a bunch of summer schools on social science research techniques and methodology, and I'm very curious. I love to explore and practice stuff.
I'm very interested in strengthening my data analysis skills, so my choice is between studying Excel for Business or learning Python basics. I have a basic knowledge of Excel and zero about Python or programming in general. I have a certain grasp on calculus and statistics, even if my university courses aren't heavily focused on these subjects.
Excel is a very common tool, universally present in every company, in every sector. Also easier to learn [just maybe?]. The online course is 4 weeks long.
Python is more complete but also complex. It could also give me the chance to access larger sets of data and automate stuff. The online course is 7 weeks long.
I don't know what position I'll be looking for after university, but I aim to have as many as possible job opportunities. My fear is here in Italy few employers know about Python and how to use that in business.
But somehow, my gut says that Python could be the right choice. What do you guys think?
In your position I would definitely choose Python, because:
you can program outside a software suite.
it is a stable environment. VBA tends to crush or to do mysterious creepy things.
it has a huge, active community, compared to VBA.
it is well maintained and documented programming language.
it has tons of useful libraries.
it will be the top programming language for the next years
knowing Python allows you to program stand-alone executable programs with nice GUI, do data science, machine learning, web frameworks, signal- and video processing, work in a scientific environment [Jupyter], learn to hack and even create games.
Python works the same way on Windows, Mac and Linux, also on RaspberryPi and I even have a Python distro with Jupyter on my Android phone
So python gives you an enormous potential to strive for whatever you like. VBA on the other hand is in decline. Microsoft 365 especially MS Teams works already with JS and not VBA. It will sooner or later be deprecated. Of course it is good to program nice macros for Excel or Word, but you can do the same stuff even better in Jupyter or in your own GUI Python program. I tried to so some Word-macros [splitting documents, etc.] and it was hard, because there are not many sources out there. The MS documentation - you have to say this - is BS and crap, and worst it is outdated. The only thing that will help you is inside the VBA editor, but this is still nothing compared to the python environment. There are no books published in the recent years about VBA for Word... I am forced to use a book written for Word 2007 & 2010!?
So to sum up: Python is your fishing rod, VBA is the suffocating fish on the river bank that will die soon.
Forgot to add: with Python you can also do Linear Algebra, FEA and symbolic mathematical calculations.