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 started programming in early 2019 doing some basic tutorials on, and discovered that I really enjoyed writing code! It was like one big puzzle, creating and moving pieces around until you accomplish some goal. I started with simple HTML and CSS, and then moved on to JavaScript. I was having a lot of fun, but I also knew that this was only the tip of the programming iceberg. JavaScript was my first glimpse into what can actually be accomplished with code, and it was at this time that I started to get really excited about code. I decided to do some digging to find out about all the different areas of computer programming and what jobs were out there. Turns out, the job possibilities for developers are endless, but also so are the skills required for the job. I saw developer job postings for companies that I had been dreaming about working for since I was in high school. After looking at the preferred qualifications for a lot of these jobs, it was clear that if I wanted to seriously get my foot in the door at any of these companies, self-study was not going to cut it.

In November of 2019, I enrolled in Code Fellows — a software development bootcamp in Seattle — and started exploring the world of software engineering first-hand. We focused mainly on front-end development and by the end of my time at Code Fellows I was able to code full-stack CRUD applications in JavaScript using a variety of different libraries and third-party APIs. During this process, I came into contact with a lot of structured and unstructured data.

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.

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