No this is not a tutorial for getting your first web app up and running, and for the most part I’m going to stay away from web app related topics. But, as this is my first Medium post in the data science realm, I thought I ought to have some sort of introduction to me; who I am, where I come from and my path to data science. If that sounds boring, topics involving python libraries, manipulating/storing data, modeling/neural networks, data science concepts and trends, artificial intelligence and more will be posted shortly. However for those interested in me and my background, read on!
My name is Sam Thurman and I am a software developer with 6 years experience in music production and recording using Ableton, Logic Pro, and electronic instruments such as Omnisphere and Serum. I got started promoting artists for a company called HOF is Better in Sacramento and later, started promoting and hosting events through the DNA Lounge in San Francisco. I have been promoting and managing artists in the Bay Area and Seattle for over two years since, and have had the opportunity to meet some amazing people along the way. I have a passion for providing creative solutions to problems and love engaging people through creative collaboration. Being in collaborative spaces with a wide variety of people has given me an opportunity to learn how to explain concepts, ideas, and results in many different ways.
I have always been interested in trying to extrapolate meaning from data, and even though my goal was to simply retrieve data and display it, I found myself more interested in trying to understand the data I was getting, and trends associated with it. This, at its essence, happens to be the whole problem domain Data Scientists live in. According to Chikio Hayashi — one of the early pioneers of the field — Data Science is defined as “an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data.” Basically, data scientist answer the question of how data can be used to understand past behavior and make informed decisions for the future.
I started looking into the day to day activities associated with being a data scientist and realized these were things I was good at, or at least would like to be good at. Gathering, looking at and shaping data were the major facets of Data Science; but what you do with that data was the interesting part to me. It seemed that basically, data-scientists are the go-to people when it comes to figuring out — from data — how to optimize some process or improve on some problem area, and this was really interesting and exciting to me. Aside from just being able to help a business improve, data science is also the key to improving the scope of what computers can do. Machine learning is simply the process of computers harnessing the power of big data fed to them by scientists and engineers. Artificial intelligence is just a computer that optimizes itself and learns over time, and the fact that you could create this type of process using data, was extremely appealing to me. For all of these reason, it seemed like Data Science was the place to be at.
In January of 2020 I found Flatiron, a bootcamp with a campus in Seattle offering a 15-week data science track. I was impressed with the curriculum outlined on the website, it seemed to focus on everything I wanted to learn: working with structured and unstructured data, working with big data, tools to use for statistical analysis and visualizing data, and even machine learning.
After talking to faculty and some currently enrolled students, I applied for admissions and now find myself with four weeks until I graduate. Post-graduation I plan to begin searching for a job as a data engineer and currently have a goal of working at Spotify or Tidal as a Data Scientist/Music Analyst.
If you made it this far, thank you and congratulations! More (technical) posts to follow.