My Story before studying data science 💾
May 05, 2020
Now tends to be unclear which way to go, but every step was indispensable when I look back
I grew up in South Korea until my high school years. After high school, my family moved to U.S. I always wanted to be a pilot and so I started the pilot program in Baltimore. I ended up transferring to Aerospace Engineering in Univ. of Maryland because of tuition. I never knew it cost a lot to be a pilot!👨✈️
Aerospace Engineering 🚀 was cool, but I did not enjoy my college years. Back then, learning environment was great but I did not realize how beneficial it was. I had quite a lot of math, physics and computer classes, but did not enjoy them. I did not like my classmates sitting in the front and ask bunch of questions because our lecture ended late. Now I respect him, because I realize now asking a question is crucial for learning new stuff.
Somehow I went to graduate school in Aerospace Engineering but I totally failed in experiments. To be honest I did not deep dive into this smart material research. I alwasy tried to find reasonings why to learn this at this specific moment. I did not know how to enjoy learning, and my friends did. I regret that a lot.
Career in Engineering ⚙️
I came back to Korea and I started my first career as Hardware Engineer in Smart Valve Control Lab. I did handle lots of PCBs and soldered samples a lot. There again, I had a chance to go deep dive into this hardware and embedded sw area, but I did not. I only had a interest and did not have disciplines. I was not so much crazy about this embedded software, excusing myself that there are not much resource out there.⚙
Then I got a job at Korean Air as a System Engineer, development in UAV. My major was this airplane thing so I was excited. The company was big, and my role was small. I was bored quickly and got tired of this development process thing. For the security reason, we had no internet access in our office and we had to print out our excel sheets to submit to Goverment. There also, I had a chance to expand my knowledge in computer vision. I was in charge of vision-based self landing project, but I failed to find the right estimation algorithm. I did not understand Kalman Filter enough to start my own project.
Career in Sales 📈
I quit my job and wanted to learn sales and communication. I thought I was strong in communication but was not able to utilize it in Engineering Field. (not i think it was wrong, but back then I did think communication was not used in my field) Therefore I started my new job in Technical Sales in Atomotive Embedded Software. I really enjoyed my job, meeting customers and presenting technical stuff to audiences. I learned communication a lot during my 3 years of sales career.
I again got bored by getting paid. I did start airbnb thing but instead of bedroom, I offered dinings to those who visit Korea. I gathered couple more hosts for dining sharing service. I recruited a team. Me and my friend failed because we did not attempt more aggresive next steps and we did not how to efficiently manage our main operation tasks.
Learn Web Dev 💻
The reason I think I faild on my first business was that I did not know Web Development domain. Therefore, I learend web dev skills in coding bootcamp for 3 months. It was not enough, but it was enought for me to start as a developer in the field. I did some freelances jobs and worked in a startup for 3 months. I started my own small business again, flower delivery with my web dev skills. (I used slack as a order server, serverless! - as expected I missed a lot of order request because of losing communication in between slack APIs and my react web app).
Career in Education 🎒
I was getting paid by the bootcamp by helping other students whil I was running my own business. My intereset was naturally moved to Career Education. CEO asked to run this bootcamp together and I accepted it. In the beginning, I did not now where to start so I just spent a lot of time stting next to the students. Then I learned it was not so efficient, so I designed more flip learning systems. I asked my colleagues to record the lectures and started spending our live times for questions and discussions.
The big change was moving offline to online. The online learnring environment was not so familiar and we had many resistances from the students in Korea but we did not stop. Eventually, we facilliated this online learning system with our own Learning Management System. We grew quickly and got our pre Seris A funding.
Thinking about Data 💾
So wer are growing and our operation cost was proportionally getting increased as well. Students were not getting the right education metrics for themselves and we did not have the right metrics of them. Therefore we could not provide quantitive comments for our students and that led our partner hiring compnay’s low satisfactions.
We started analyzing data flow in our business. From the admission to job searching, the whole curriculum was involved student data. That was a huge surpirse to me. It wasn’t new, it wasn’t data scient, it was just that I was not paying attention to data being used.
Every colleague was handling some data, some was doing properly, some was not. Therefore, we decided to learn data no matter what position and role they have. We had a study group, and we shared our learning resource together.
That was not enough. CEO recommended to learn data science, the whole curriculum so that I can maybe share this data science knowledege to our colleagues eventually. I started learning about data science seriously with online bootcamp. This was my second time enjoy learning. First was a web dev, not data science is sweet to learn. I really hated Statistics all my life, but not anymore. It really is everywhere in our daily life and I think I can definitely apply to our education. Machine Learening will help us to set up a model and enhance our recommendation and predictions. I can’t wait for that to happen. I can’t wait to share my learning to our colleague. I’m not ready yet, but I know being ready will never come.
Therefore, I will start my draft technical blogs weekly. It does not have to be perfect or professional. My works never did, but as long as it gets better, I’m fine with that. I have a great Lecturer, Team Lead and good group mates. I believe we will become a huge networking group, and soon play an active part in this data science field.
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