Russell Martin, after completing Data Science Foundations, also completed our Applied Machine Learning online course and then joined the Data Science Fellowship for Summer 2018. Russell’s next step was to join The Data Incubator team as a Data Scientist in Residence.
Can you tell us a little bit about your background?
I’ve always been interested in Mathematics, and found that I had a certain knack for it. So my educational and professional background is really based in Mathematics – I studied for my Master’s at Clemson University and my PhD at the Georgia Institute of Technology, both in Applied Mathematics. Then I returned to England for my Postdoctoral research, as a Fellow at the University of Warwick. A few years later I was able to secure a position at the University of Liverpool there, as a Lecturer – equivalent to an “Assistant Professor”, here in the US.
How did you find TDI’s Data Science Foundations, and what made you decide to try it out?
Did you take any other online courses from The Data Incubator?
After completing Foundations, I decided to continue with the Applied Machine Learning course. The course was challenging, especially being in the UK at the time. While the course runs in the evenings for US time zones, it ends up being about midnight in the UK. So it was really helpful that the live lectures were recorded, in case I had to go to bed early on a certain night or if I felt like I missed something during a lecture. I found that the Machine Learning course really built on the knowledge and skills I had gained from Foundations.
Did you know about TDI’s Data Science Fellowship program before taking our Foundations course?
Yes, I knew about the Fellowship but I wasn’t necessarily planning to apply when I joined Foundations. I was planning mostly to stay in academia and utilize my data science skills to benefit my academic research work. Becoming a Data Scientist was something I had considered but hadn’t really been pursuing. However, taking these online data science courses very much solidified my interest in pursuing data science as a career, outside of academia. So I decided to apply to the Data Science Fellowship Program.
Did TDI’s online courses help prepare you for success in the Fellowship?
Definitely. Prior to the Data Science Foundations course I had no experience with pandas dataframes. The Fellowship curriculum, as well as the online courses, is based in Python and pandas is one of the primary libraries we use for data analysis. Also, I became very familiar with workflows for machine learning through the online courses. This is another central concept that is taught in the Fellowship. Having prior experience with each of these things really set me up to be able to come into the Fellowship program without having to start fresh and learn all new concepts while working on implementing them into projects at the same time. In the later weeks of the Fellowship, we learned a lot more things I wasn’t so familiar with at the time – but having that background already really helped with learning those new concepts even more quickly.
Lastly – tell us a little about your new job!
I’ll be joining The Data Incubator as a resident Data Scientists and instructor, actually – in Washington, DC. When I was accepted into the Fellowship, TDI reached out and asked if I would be interested in working as an instructor after graduation. My previous experience as a professor, I think, lends itself to a career in teaching data science. And with TDI, I’ll be teaching the tools and techniques that are at the cutting edge of the data science industry.