My Journey to Data Science
Tags: beginners, datascience, womenintech, python
Published: 2022-09-26 22:53:06

My journey to data science has been anything but linear. If you asked me what I thought of mathematics or computer science when I was younger, I definitely would have said that I hated it. In fact, in the eighth grade, I almost failed algebra. Me and mathematics used to have a rocky relationship. However, that is not currently the case. Once I started giving mathematics a chance, I realized that I actually kind of liked it. What I liked most about mathematics was that there was always a correct answer, and there was usually a routine way of arriving at that answer. Unlike English & social studies classes, there was no room for debate. You were either right or you were wrong. Hi, my name is Anita Camlic and I am currently studying data science with the Flatiron School. 

During my junior year of high school, I was given the opportunity to take the first computer science course that my school had offered. It would replace my language requirement. So, I decided to trade the French language for Java programming language. It was safe to say it was the right choice for me. Just like anything, it was challenging at first. Before this class, the only experience I had working with computers was surfing the web and writing papers for school. It was so cool to me to learn all of the other things I was previously missing out on. In this class, we were taught computer science with Java. Learning Java as your first programming language is not easy. Looking back, I’m glad that I was taught Java to begin with. Java has a lot of syntax rules. Unlike python, white space isn’t an issue. The issue is the syntax and making sure you don’t throw an error due to a missing character. I learned a lot of basics of computer science in this class. Though it challenged me a lot, I think it was necessary and pushed me to be where I am today.

After high school, I attended the University of Connecticut from 2016 to 2020. At the beginning of my college career, I was just going with the flow. I was undecided and taking any and all courses that seemed interesting to me. However, towards the end of my sophomore year, my guidance counselor warned me that if I don’t declare a major soon, I might not graduate on time. So, it was time for me to decide. I thought about my past, what I liked, and what I didn’t like. I came to the conclusion that I didn’t really enjoy writing, but I did enjoy working with numbers. Ever since middle school, I’ve liked the reliability of mathematics. So, I majored in applied mathematical sciences and minored in computer science. Throughout my undergraduate education, I liked my classes but none of the classes really stuck with me. I would always hear people say "math isn't a life skill", or "another day and I still haven't used xyz math class”. For a while, I was unsure as to how I would use all of the theoretical mathematics I was learning in the real world. I never really saw the applications of my courses in life, and therefore, I began to think that maybe mathematics didn't have a big place in my future after college. That was until my second semester of senior year, that's when everything shifted for me. During that semester, I took two courses that interested me beyond belief. These courses really changed how I viewed life, and my future. Those classes were Cognitive Science and Introduction to Machine Learning. Cognitive Science is a fairly new field. Google describes cognitive science as “the interdisciplinary, scientific study of the mind and its processes with input from linguistics, psychology, neuroscience, philosophy, computer science/artificial intelligence, and anthropology”.{% embed https://en.wikipedia.org/wiki/Cognitive_science %} I enjoyed that class, and it helped me to understand practical and useful applications of artificial intelligence. I was apprehensive about taking Machine Learning. It felt like everyone in my class was more capable of success. I went in blind and I instantly felt behind when class started. However, there was one aspect of the class that gave me hope. My professor was a Woman. This was pretty unusual. When I was in college, most of my mathematics and computer science professors were Men. Most of my classes were made up of Men. There’s nothing wrong with that. But, in such a male dominated field, it’s easy to get discouraged if you don't see representation. My professor was like a ray of light. She helped me picture myself maybe being a machine learning engineer or a data scientist someday.

If I’m being honest, Machine Learning was a difficult course. It was challenging to wrap my head around concepts like neural networks and mathematical operations on high dimensional matrices. Unlike other courses, my frustration and confusion only fueled my desire to learn and understand. Machine Learning was the perfect combination of mathematics and computer science. There is a lot of logic, which I love, and a lot of statistics, which I learned to like. It all eventually blends together to something so intricate and beautiful. Ever since graduating, my interest and love for machine learning, and the broader field of artificial intelligence, only grew stronger.  It grew so strong that it led me to the Flatiron School.

I particularly like the applications of data science that are making the word a better place. For example, you can use data science to monitor surveillance data, and flag for a threat in real time. This is one of the applications that can potentially save lives and keep people safe from unnecessary violence. Another application or data science that is also making the world a safer place is autonomous cars. It has been shown that computer vision models for autonomous cars react faster to an obstacle in the vehicle’s path because computers can read the visual data and react faster than humans can. All of these seemingly futuristic things are real, and occurring. On the other end of the spectrum, I also enjoy the fun applications of data science like recommendation systems. I think it’s the little things like this that make people’s days less stressful, and more convivial. I find joy in these systems and I would love to one day be able to see the backend of the systems and help improve them. Some of my favorite examples of these systems are the Spotify music suggestions and Netflix show suggestions. Their recommendations are almost always spot on. Regardless of the application, data science is changing lives and changing the world. I believe that data science is the future, and I want to be a part of it.