Blog Post #5: Course Reflections
The semester is coming to an end and as I reflect on what I will take forward, I find myself a bit amazed at all that I’ve learned in a few short months. When I started the semester, I was cursing R/R Studio. It felt like I couldn’t do anything at all without installing more and more packages. Now I find it very intuitive to use (with the possible exception of R Shiny which I still need more practice with).
Besides learning the R language, however, I am excited about all of the data science techniques that were included in this course. When we first started project 2, I had to Google the acronym EDA. I’d done EDA-like work in practice before, but I enjoyed reading about different techniques and formats for doing EDAs more formally. I also thoroughly enjoyed the modeling section of the course and enjoyed learning about so many different machine learning techniques that I had maybe heard about somewhere but had never formally learned.
My goal when I complete this program is to take a role that is heavily focused in solving problems with advanced data analytics. My only formal coding training prior to this program was a (now archaic) programming course that I was required to take as an undergrad. At the time, I wrote off programming as a skill that was just too tedious (due to lack of user-friendly interfaces at the time, I believe, I would spend hours upon hours debugging). I learned more programming languages when I worked as an engineer, but was stretched too thin to go after the advanced techniques. Now that I’ve put more effort into learning languages, I feel like data science is a career that I would be really good at. I think my previous experience working to solve problems with data as an engineer in industry gives me a really good background for pursuing data science further.
Since the field of data science is so broad, I know that I still have a lot of things to learn. Next up on my horizon is ST590 (Big Data/Python) which I’m really looking forward to taking next semester. Along with that, I plan to teach myself Tableau as well as dive deeper into SQL. I thought I knew SQL pretty well, but I discovered that I still have some gaps when I was trying to help someone with a project recently. One of the best things about data science is that the field is constantly evolving and I don’t think there will ever be a shortage of things to learn.