My experience with Flatiron School’s Immersive Data Science Boot Camp — Part I

Edit (2/22/2024) : I’ve had a lot of people reach out to me asking about the program, so in the interest of transparency, and helping you make an informed decision I've dropped the paywall for all Flatiron stories and added a link to the next one at the bottom of each story.

I’m a recent graduate of Flatiron School’s Immersive Data Science Program. I joined this program as a way to develop a set of hard skills I could use to change my career after getting laid off from 10 years in the Wealth Management industry first at JP Morgan Chase, then at UBS. I left that industry with a hard earned core set of skills that revolved around financial planning and sales.

At the start of my career I was a hardcore introvert, unwilling to leave the house unless I absolutely had to, and having extended conversations was both difficult and exhausting for me. I finished in 2018 with the ability to walk into any room and build solid foundation towards a lasting relationship with whomever I was meeting with. Some of my clients from my earliest days in the industry still reach out to me today, and I am proud of that. My problem after getting laid off was that this was a soft skill, I couldn’t put it on a resume and be convincing about it. I had to get in front of someone to prove it, and for whatever reason, my resume wasn’t getting me the face to face interviews I needed to prove it.

The Search Begins

After almost a year of applying around with nothing to show for it, I resolved to change careers, and this data science thing everyone was talking about seemed to be the ticket. It promised wages close to what I used to earn. It promised skills I could keep and use in almost any industry. It was the hot new job, and there were thousands of positions open for it in New York right now, rather than the 3–4 I saw for my old role.

So I resolved to try a boot camp. But which would I choose? An internet search brought me to coursereport.com which reviewed a large number of boot camps. I saw General Assembly, I saw Udacity’s online course, Brainstation, Galvanize, and dozens of others. I saw a lot of reviews for the data science program, some good and some bad. Some featured a job guarantee, others did not. It seemed the course curriculums were largely similar so I resolved to pick one that at least had a job guarantee.

A friend of mine had taken the software developer course at Flatiron and raved about her experience. She loved the curriculum, and she especially loved the community that she was educated in. She made it a special point to mention that Flatiron was picky about who it accepted, that students had to meet a minimum threshold of baseline abilities in order to get in. This to me made sense, since the school put its money on the line, it was best to rig the game with applicants most likely to pass the material and land a job. The problem was, I couldn’t find a single review of Flatiron’s Data Science program, it was like they didn’t even have a program despite all I had heard. The closest I found were people reviewing their free online intro course, and most found it largely helpful. This wasn’t going to help me determine how well the course was run and whether or not people experienced success from it.

The Interviews

I decided to give Flatiron a try despite the lack of reviews, but was determined to discover why I couldn’t find a review for their full Data Science course. The reply to my application came in the next day with an invitation for a one-on-one interview via Zoom, where they would ask me questions as a get to know you phase. They asked questions like “What’s a problem you encountered in your life or work that you had to overcome?” and “How would you react if some code you wrote was broken and how would you overcome it?” For me, mistake are learning opportunities, so I believe they liked that answer. I made a point of mentioning that I couldn’t find any reviews of their Data Science Immersive program, and my interviewer said that was likely because their program was barely a year old at that point (June of 2019). Lastly I asked that many data science job postings I had seen made a point of requiring that candidates have at minimum of a master’s degree in a hard science, though a PhD would be preferred. Given these stringent requirements, how could a graduate expect to be able to find a data scientist position if Flatiron wasn’t handing out Master’s or PhDs in Data Science? My interviewer acknowledged that many job requirements did feature these requirements, but that Flatiron was prepared for them:

1. Their career placement programs would help us find positions that didn’t necessarily have these hard requirements.
2. Many of the job postings with these requirements were actually “nice to haves” but not really a hard pass.
3. That the portfolio of projects we were set to complete in the program would argue that we were just as qualified for certain positions over those who had a Master’s or PhD, because we had real world examples of work that would be useful to these companies.

The interview was followed up the next week with a technical interview, again, conducted through zoom. I was given the introductory boot camp course to review, and to be prepared to do some live coding and answer questions based on the material. The intro material was dense stuff, and while I’d had a brief introduction to Python from Code Academy, I was introduced to completely new and KEY concepts to Python that I had to rapidly assimilate into my coding mindset. The material also skipped around, so in the first chapter I was building lists of dictionaries, and then 2 chapters later i’m writing For Loops. The problem there was that there were some pretty key topics between making a dictionary and building a for loop that were simply skipped to provide an overview of the actual curriculum, CRUCIAL topics. When it came time for the technical interview, I’ll be honest, I struggled with it, but managed to complete the live coding, which was fairly basic. Then we moved on to the math component, for which I was NOT prepared, a review of basic statistics and identifying key parts in a derivative formula from calculus. I admitted I hadn’t gotten to that part after giving up on the For Loops section, and we rescheduled our interview once I had covered those parts.

In the end, I was deemed worthy of joining Flatiron’s program. They sent along a list of online courses as pre-work. The list was comprised of beginner to intermediate courses in Python, SQL, terminal commands, statistics, calculus and probability. Its purpose was to provide a baseline competency in the upcoming curriculum to even out the varying degrees of experience amongst the incoming students. This coursework is intended to take anywhere from 2–3 weeks to complete, but really i’d recommend you take a month really going at it to make sure you understand everything and can replicate it.

All in all, I was given a pretty hopeful picture of what my future prospects would be as a data scientist through Flatiron. Next week, I’ll go over what my first few weeks looked like and what I learned. See you all next time!

Follow the link for part 2!

https://medium.com/@hammychang/my-experience-with-flatiron-school-part-2-aa05869efc7e