What I Learned From My Three Degrees

Key Takeaways

well everyone can hear about another exciting video for you today I'm talking about my educational journey what I learned with each degree and how those all set me up for a career in data science as usual please hit that like button if you enjoy this video and if you'd like to see more content like this please subscribe alright I'd like to start with college because for most of high school I was kind of a waste of space so I wasn't I wasn't very focused and things really took a turn after a couple years of college when I started to study things that I was actually interested in and that took a long time I had a lot of different majors I studied psychology environmental science health and exercise science the Business Administration a whole host of things and the first time that I actually took a course that I liked it happened to be an economics course the way that we were learning we were seeing the world and we were singing trends in a very different way than I had understood them before we could actually model the world in terms of math in terms of supply and demand and we could understand how people function like what they're actually gonna do and how markets work which was very fascinating to me ever since I took that class I had been you know I was I was struck with this way of looking at the world and I continued on that path so I graduated with you know my Bachelors of Science in economics and I think I minored in business as well and this has been that experience was really good because I got a basic understanding of Statistics and I also got a different way of thinking out about the world I started to think about the world more quantitatively rather than just kind of observing individual instances of what was going on I could look at the big picture rather than making all of my assumptions based on small amounts of data and you know that's really for me an important part of data science you're looking at the data as a system you're looking at the big picture a lot of the time and you're trying to make evaluations based on that there are you know small data models and small data algorithms but for the most part you're looking to try and understand big picture trends and to capitalize on them after graduating college I unsuccessfully attempted to play professional golf and it was a great and fun experience but I did not make any money so I decided that I wanted to go back to school I was really interested in becoming a management consultant and I wanted to do that because I thought you know those people came off to me as people that were thinkers they were problem solvers and that you know that was very appealing to me especially with my new worldview so I went and I got my masters in global commerce which is a global business degree and I picked up some technical skills so I learned some sequel I learned how to do some basic statistics and are I also learned how to work in a team and how to actually go about communicating the work that I was doing or tell a story telling a story about a project or solution that we had come to this was where I started the foundations of my interest in data science I think telling a story is extremely important in data science I also think you know understanding technical skills manipulating data is is integral to success in the field and at this time I'd also started to get really into sports analytics so I was focusing on applying everything that I was learning in this sports role though I didn't have a ton of success in the short term there but this did start the ball rolling to develop my career in sports data science after graduating I did end up working in management consulting for about a year and honestly it wasn't exactly what I thought it would be there's a lot of hours of doing kind of groundwork I wasn't thinking as much as I was hoping I still had this you know great passion for sports for analytics and I felt that I was reaching a roadblock with my technical skills so I researched and I wanted to get a better understanding of programming languages as well as a different way of thinking about problems so I went back and I started my master's in computer science this degree was absolutely different than anything I've ever learned before you know it's a lot more technical I hadn't had any programming experience so I absolutely had to really study hard and grind to be able to keep up to speed I did find that I that I liked programming that I liked computer science and that it was very different from the educational experiences that I had before computer science was fairly solitary we didn't do a ton of group work and the problems are relatively relatively binary so either your program works or it does it in business school in college you could get partial credit you know you if something was close or you could sell the teacher you would get points but in in this scope of study it was very black and white which was a very different perspective and an interesting perspective for me in this degree I learned a whole lot of different things mostly technical skills but I learned how to work with sequel I learned Python or Scala C Java and a bunch of different language languages I learned how networks work how databases function how frameworks like MapReduce work and you know that was in my mind like the next level in terms of understanding how to do really high quality data science so data science is obviously heavily focused on thus it has statistics and the math but in order to be a really good data scientist in my opinion you have to be able to implement what you're doing and make it a product make it into something that's usable by people I'm also very interested in entrepreneurship in general and having a background in technology is really valuable you know being a creator rather than someone who supports is very very freeing in my mind it's something that I really appreciated learning about in that degree I chose to go the Masters in computer science route over the master's in data science route because of those entrepreneurial ambitions that I had I thought that it was easier to you know saw myself as a technical partner or to be able to actually spend something up if I had that broader background I did concentrate in artificial intelligence and machine learning though so I took mostly those courses but I still have this the core software engineering networks and systems courses that any computer science students would have for me going back to school the second time I think was one of the best decisions that that I've made I was able to learn a whole lot I picked up these technical skills that I might not otherwise would have gotten I also have a learning style that lends itself very well to the classroom that's something that I knew if I try to learn this on myself I wouldn't have as much success because of just how I learn and how I work I think for many other people the formal education route might not be the best approach if you're really a self-starter and I know there are a lot of them out there I think the quality of courses the quality of material outside of the formal setting you know anywhere on the internet on YouTube on udemy Udacity EDX all these websites is the same quality if not better than you'd find in university setting there just isn't that formal structure that encourages you to work on it all the time for me I kind of need someone kicking me in the butt to make sure I do my homework and to turn things in on time and apparently I have to pay for that I think it goes without saying that this computer science degree was the most important educational experience for me in order to become a data scientist because of this I was able to talk the talk and inevitably walk the walk in the data science realm I learned basically all of the necessary skills and I was able to practice them on projects and an internship etc you know one thing that a lot of people don't think about when they're there in school is that you're you can do internships you can get a bunch of different job experience while you're doing it and you can kind of double your your learning your capacity because you're putting into practice what you're learning at the same time and applying your knowledge is in my opinion the best way to learn having a project having a job it just it's just reinforcement all the way through obviously like where I am now I'm able to help a lot of people get into the field and help them learn about my experience in data science if I could go back I would probably change a couple things to really maximize my potential I think that if I had studied something a bit more technical in college if I focused on computer science math physics or you know something slightly more intellectual that would have paid dividends in the future when I learned computer science so late and my you know my third degree I was never able to get as good a grasp on it as some other people who had learned it earlier I kind of speak it you know when someone learns a language late in life they usually have an accent I kind of think of my computer science knowledge as having an accent and you know it does give me a little bit of different perspective but again it does not come naturally when I program or want to put together application you know something else that I would have done differently as well is have focused on my organization so as a student I had a bunch of different projects had a bunch of different homeworks and that's all great content for me to be able to share with potential employers to share with others to help them understand the subject better I was fairly disorganized I didn't have my code in a repo and you know that's something that I really wish I had together more organized now I've gone back I've put some of it together but when I was writing it if I took better notes if I had you know had better comments etc that of really you know done future can a huge favor the last thing that I think I would have done a little bit differently is I would have loved to stay in touch with more of my classmates and with my professors and the whole staff at all of the schools you know I felt like I was treated really well at every school that I went to and you know I I'd love to be able to continue those relationships to be able to get back with educational content or you know potentially even with money in the future you you have a great Network through schools your professors your you know employment centers etc can really help you out and connect you to the correct people I know that whenever I'm pitching the business or trying to grow something that I'm working on it's usually the people from my academic networks that reach out to first you know people that I've done a school with also reach out to me and it's great to be able to share and talk about that that one thing that we have in common one final note although I do have two masters degrees I don't think a graduate degree is really necessary to become a data scientist or to become a high-level talk to your data scientist I really believe that the quality of your work is more representative of your skill then how many degrees you have and if you do really good work you documented well and you're constantly learning I think that it will take you just as far as any degree will period thank you so much for watching and - have a great one