Experience with: R - Python - HTML
After browsing through this website, you might ask the question how I even ended up learning to program. Short answer – efficiency. Long answer – I don’t like inefficiency. And programming makes it possible to be way more efficient when performing mundane tasks, even making some tasks possible in the first place.
I got into programming when I was writing my Master Thesis. I already had all the data evaluated in Excel, but I knew that I would for sure not like to analyse anything with several tens of thousands of data points anytime again using Excel. Evaluation of anything beyond a couple hundred of data points is slow, I saw a lot of potential error sources and the process contained an awful lot of repeating (boring) tasks. I figured, that as I already had a real-life dataset (which I knew very well, as it was me who designed the experiments and performed them to obtain it) that was already evaluated and checked by a colleague, I could learn to code in R and use the results I already had to self-check if what I was doing was correct. I ended up re-evaluating all my data in R and producing all my data-relevant figures in it.
As I was really fascinated by the newly discovered world of programming, right after I finished my Master´s programme and thought about what challenge to tackle next, I dived into Python. As I am particularly interested in exploratory data analysis, I chose to do a couple of certificates that would teach me that. After finishing two courses I thought that the best way to present my skills and interest would be by showing it on a website, so I started working on this website in HTML with CSS and a little bit of JavaScript to top it off. As I only started in 2019 with programming, I know that there is yet a lot to come, but I can clearly see the advantages of it in today´s (scientific) world.