When Brandon Beidel decided to transition from software engineering to data science, he considered both in-person and online bootcamps, but landed on the latter option. During his search for the perfect program, he identified a few important factors: flexibility, mentorship, and career services. Springboard’s Data Science Career Track stood out and Brandon now has begun his first job as a data scientist.
Course Report recently spoke to Brandon about his life before, during, and after Springboard.
My undergraduate degree was in economics and I did not have any programming experience in school. I started out working as an analyst at a consulting firm, but as time passed, I often worked with software developers who were doing really deep technical analysis. They were using software as a tool and I wanted to learn more.
I’m actually a two-time bootcamp graduate. To transition from an analytical role to a full-time programming role, I attended a full-time, in-person bootcamp called Codeup in 2014, where I learned the LAMP stack. I got to work as a web developer and I’ve written in a few other languages since then. But data science seemed to be that sweet spot between thinking about a problem in a truly deep analytical sense and having the tools to actually act upon those thoughts. I wanted to solve problems using software and machine learning as a tool.
I did. I definitely used some self-guided online resources like Data Camp, but in my learning experiences, I’ve really valued having a dedicated mentor, which I had in my previous bootcamp experience and which Springboard offered. The mentorship was really the big selling point for me.
I was looking for a data science bootcamp to help me make that transition. I had done some self-study, but ultimately, I’m a big believer in setting aside a few months and really dedicating it to learning a new skill. I knew the value of setting aside the time and really immersing yourself in a topic.
I had considered some in-person bootcamps, but at the time I lived in a very rural area. Making a four-hour trip to New York or another major metro area wasn’t an option. Whereas at Springboard, it doesn’t matter where you learn from, as long as you have an internet connection and put the work in. I didn’t consider any other online programs—Springboard was already on my radar.
Springboard had the four factors that were the most important for me: the ability to learn remotely, the ability to have a flexible schedule so I could still work part-time, dedicated mentors, and career services. They did a really good job providing me a structured way to apply for jobs all over the country and ultimately helped me find something that piqued my interest.
There was a coding and statistics entry exam, which took one or two hours. They provided some resources to prepare—exercises in Python and some statistics questions. I wasn’t super comfortable with Python at the time, so I had to brush up on syntax. It had also been six or seven years since I had been in a statistics class, so I had to find some resources for that as well. I spent one weekend studying.
It was a mixture of external resources they had curated, along with custom teaching. Throughout the week I could set my own pace and decide which exercises to complete. At the end of the week, there was a 30-minute call with a mentor, where I had the opportunity to ask explicit questions about things like career experiences or specifics about machine learning. The questions varied as I went through the course.
Springboard did a very good job listing out how much time to expect a particular task to take. I could plan my week in advance and say, “Here are three things I’m going to finish this week. It’s going to take me 20 hours, and I need to be ready by Saturday for my 10 a.m. call with my mentor.”
It was pretty much a rinse and repeat cycle every week. I would come home after work and work on those things through the evening, maybe four or five hours a night. And then on Saturday, I would work through any problems with my mentor—anything I was stuck on or confused about or just wanted to dig deeper into.
I was working part-time on some software development contract work while completing the course.
I tried to stay pretty regimented. Between 9 a.m. to 5 p.m., I worked. After 5 p.m., I did Springboard. In fact, I would even move to different locations and have different computers so that the worlds did not collide.
Yes, in a couple of ways. There are online forums where you can ask questions of your fellow students about the curriculum and ask for input from people who might be further along in the course. I also made deliberate attempts to travel to some nearby metro areas, like Washington, DC, New York, and Philadelphia for some long weekends, to meet up with some of my fellow students in person and attend some networking events. Part of Springboard’s curriculum actually encourages students to go to data science meetups and make sure that we’re not just learning the curriculum, but actually talking to people.
Springboard gave us checkpoints throughout the course. I went through a series of explicit exercises and conversations during the curriculum to help narrow down the types of roles I was interested in, the cities I wanted to work in, and the industries that interested me. Before I sent out a single job application, I had a shortlist of 20 companies to start looking at.
On top of that, they gave us opportunities to practice presentation skills and interviewing. Springboard covered the whole life cycle of the job search, not just, “How do I push my resume and get myself in the door?”
I finished Springboard in four months. Springboard recommends taking six months, but I intentionally wanted to push myself to finish it as early as possible. I looked for a job for about six weeks. I had an offer within a week or two of completing the course, but ultimately decided that it wasn’t in a location I wanted. It was very affirming to get an early offer, so I felt confident in being picky and taking my time with it.