A Journey into Data Science
A Fascination Begins: Reminiscing on Progress
My fascination with all things computers and technology began in the late 1980s. It was mainly for one reason: computer games. All of my friends in the neighborhood had their gaming computers, which at the time were Commodore 64s (C-64 had really cool commercials). One even had an Amiga 2000, the premium line. I remember my excitement when my parents bought me my first PC. It was a Commodore Colt with an 8086 processor and 640K of RAM and I hated it because it didn’t have any games or a hard drive—or even a 3.5-in. floppy for that matter!
Anyway I slowly began to use the Colt and get acquainted with it. I remember booting up MS-DOS, seeing in the manual some instructions to create a text file, and following the instructions. I made my first file, complete with actual text, and got the computer to print it on the monitor in its entirety! That was my first taste of my journey into technology and I loved it. I put that old Colt through its paces over its lifetime as I learned to use the command line, as well as programs like Lotus 1–2–3, WordPerfect, and PKZIP. Eventually I even got some games to play on that Colt.
Over the years my tech fascination continued as I upgraded to computers with 386 DX, 486, and then Pentium processors. Desktops, towers, laptops, PDAs, Blackberries, netbooks, iPhones, Galaxies, and Pixels. I was amazed at how quickly technology was moving, and how much more compact and portable it was becoming.
I remember the internet as it progressed from dial-up AOL, DSL, and cable. From those bulky 9600 baud modems to cable modems, switches, and routers. Just when you think internet speeds couldn’t get any faster, they doubled then tripled. Speeds today are still going faster and faster. Web browsers are becoming more sophisticated, especially in the privacy department.
Knocking Out Some Projects
One of my recent projects the past couple of years was to create a fast and reliable network that spanned the entirety of my parents’ home. The house is quite spacious, so with only one router there were many dead spots. I found that I could extend the network to other rooms with a couple of MoCA adapters and then run routers off them. To get around a lot of limitations imposed by the manufacturers, I had to replace the routers’ firmware with custom software, namely OpenWRT and FreshTomato. All the routing is handled by a central router running pfSense. I loved every moment of that project, and I still work on network tweaks and optimizations from time to time.
Prior to that, one of my major projects had to do with my master’s thesis. A classmate of mine mentioned he was using a program called LaTeX to typeset his thesis. I really didn’t think much of it at the time. But then I began to run into problems with right-to-left (R-to-L) languages in Microsoft Word. As I searched for solutions, I landed upon LaTeX as a program that handled R-to-L languages elegantly. The only problem was that LaTeX was no word processor. The entire process required configuring every aspect of the document—from line spacing, to fonts, to margins, to indentations, to small capitals, to footnotes, to title page, to bibliography, and everything in between. And the configuration had to be written in its own code language! But when I finished I was so proud of not just the content but the aesthetics.
Those FAANGs
It’s not like I really intended to keep up with technology. It just so happened that way because technology has become so ubiquitous that it is now a significant part of people’s lives. All thanks to FAANG!
FAANG is shorthand that, as far as I can tell, originated in the financial world. It stands for Facebook, Apple, Amazon, Netflix, and Google. Over the past decade, these companies have been watched closely by the financial world for their business performance and future business prospects. The past 10 years, financial markets have basically been marked by the performance of these companies’ stocks.
When I first started in finance I had little idea about data, algorithms, and machine learning. I read a few comments here and there about hedge funds utilizing these tools to their success. Hedge funds like Renaissance and Bridgewater, helmed at that time by James Simons and Ray Dalio. So I knew that data science and analysis was being applied to the financial markets.
This Data Analytics Thing is Everywhere
As I learned more about businesses at a deeper level, I started to realize just how big of a role data and technology played in their operations. Various documentaries have reported on the extent of how valuable data is to companies like Facebook and Google and the technologies they use to predict user behavior. It’s not just tech companies either that rely on data science. Companies use data science and analysis to inform their creativity, products, sales, and advertising.
When I began to understand this better, I began to look into machine learning. After all, our smart devices utilize machine learning extensively. I noticed my smartphone becoming increasingly more accurate about predicting my routines and sending me well-timed notifications. As I became more curious about data science, I would search for people blogging on data science and I would try to follow some of their small projects on my own computer. The experience was like my first foray into MS-DOS that I described above. Since data science has its own flavor and is a much bigger field than an 1980s operating system, I was quite limited in understanding as well as time.
A Deepening Interest
My entire profession has been in sales. My dabbling into data science got me thinking about questions like what if I could analyze some of the best salespersons or advertisements and discover if there are any particular words or phrases that factor into their success. Or even if I could add clarity around the question of why people buy. There were many possible ways to apply data analytics and data science.
What did pique my interest as to a career in data science was when my wife mentioned that many of her coworkers were leaving their jobs to become coders. She didn’t mention what area of coding they were going into (and I’m not even sure she knew), but it was at that point that I realized, particularly with all the emphasis on data analysis that I was seeing around me, that data science is the future.
Equipping with a GA Bootcamp for a Career Change
So when I decided to get serious about data science as a career, I looked into various programs. With young kids and a wife that just switched to a new job, I was looking particularly at remote programs. Reputation of course was high on my list. One program that I heard mentioned in some videos made by those who were hired in tech was General Assembly (GA). I also read some good reviews on the data science program. All the coding bootcamp reviews had high regard for the GA programs. I decided to give the application a go.
Thankfully I was accepted and I have been enjoying my journey so far. I plan to made a difference in this world through data science. Whether that’s through collaborating with other intelligent peers at an awesome company, or going as a solo coder and analyst at a startup, or teaching computer science and coding—or maybe all three.
If you liked my story and want to follow my continuing journey, go ahead a give me a follow @i.johnmedina. Thanks so much for reading! 🙏
