Here we are, nearly two months into my data science journey with Flatiron. There have been ups and downs throughout, and as I sit at my desk finishing up the first module, I thought I would take a moment to discuss them.
The Data Science - Part Time track for the course is ten months of content, split up into 5 modules that take roughly two months each. The first module is Intro to Data With Python, which introduces most of what was once the Scipy stack, as well as SQL and some other useful Data Science tools. It’s a lot of content. The very first day I had a mini heart attack when I saw how much there was, thinking that all of it was due in the first week! Thankfully this was not the case, and the course load has remained steady and challenging, but far from overwhelming.
For me personally, I had a bit of an advantage early. I have familiarity with both C++ and general object oriented programming concepts. This made the first few sections pretty easy. I highly recommend that anyone interested in taking this or another similar course should take an intro to python course before beginning. It will help you transition more smoothly into the curriculum. Some of my cohort members that had less experience seemed to have a more difficult time adjusting.
The Cohort Speaking of the cohort, I was sold on the cohort system on day one and have only become a bigger fan of it as the course has progressed. I am in a cohort with around 15 other students. We communicate with each other daily, and I think many of us will continue to communicate well beyond the completion of the course. We help each other get past blockers we encounter, offer support for issues inside and outside of the course, and are just ultimately each others first resource. Helping others with problems has helped reinforce my own learning, and gives me opportunities to practice the types of communication skills I will need to show to potential employers down the road. Even better, it is helping me begin creating a network that I may need to leverage in the future. I’m a firm believer that every contact is a potentially important one!
The cohort system has also allowed us to naturally become subject matter experts for our teams in a very natural fashion. My team for the module 1 final project has members who are experts in web scraping, organizing our labor, as well as the algorithms behind our codes. We are even fortunate to have a member with ties to the film industry that leveraged his ties to get us some perspective from those in the industry! Again, i cannot stress enough how much I enjoy the cohort system.
Other Resources Beyond the cohort itself, Flatiron has provided us with multiple other resources to aid us in our journey. We have an “educational coach” who fills a non-technical support role. She is wonderfully supportive, plugging us into seminars and opportunities beyond our regularly assigned course work. Each conversation I have had with her has been constructive and I’ve come away feeling more confident each time. I can’t say that I’ve ever had a resource quite like this in any other academic pursuit.
We are also assigned an instructor. Ours is one Eli Thomas (you can find his LinkedIn here) He meets with us as a class twice a week, then one-on-one at a time of our choosing once a week. He has been equally as valuable as the cohort in my eyes. I can’t speak to how other instructors may be, but Eli has an energy that is just infectious. In our one-on-ones, I have been able to be completely open about my struggles in my own life and how they do or do not impact my progress in the course. He has been able to communicate on my level about them and is always willing to go out of his way to make sure that I have whatever I need to be successful. One week he stayed in call with me for more than an hour over our scheduled time to work on an end-of-section project that I was having particular difficulty with. We begin every session with an honest discussion about where I am in my coursework and develop realistic plans that allow me to succeed. I really cannot praise him enough. Whatever Flatiron is paying him, they ought to double it.
Beyond this, Flatiron also offers the ability to schedule your own study groups and chat sessions on their learn.co website, as well as recordings of past study groups with your instructor as well as others. I haven’t had much need to use these resources so I can’t speak much to their usefulness, but every extra resource is something to be appreciated.
The Focus on Employability One of the biggest reasons I chose Flatiron was their apparent focus on making sure each student can find a job after course completion. Through the end of module one, I can say this focus seems to translate into the approach to the course. There are several small projects with real world applications throughout the sections, and the SQL section even included mock interview sections. It was great to see that. This focus has been reaffirmed in our final project for Module 1. In this project, we are asked to do our own Exploratory Data Analysis (EDA) from scratch, possibly including gathering our own relevant data. Upon completion of the EDA, we are preparing a non-technical presentation of our findings including business recommendations and meaningful data visualizations. We are also required to adhere to industry coding standards, with proper documentation throughout our code. The end product is something we can feel confident including in any CV or GitHub.
Moving Forward Moving forward in the course, I feel confident that this course was the right choice for me. I have every reason to believe that by the end, I will have no trouble beginning my data science career.
Our next module is going to have a very heavy mathematics focus, including probability models and some calculus. I’m extremely excited to get going! I’ll post again towards the end of that module, if not some time before!