• UPDATE on 7/16/16: I’m heading back to DePaul University to finish what I started! Johns Hopkins is/was extremely chalenging all while working full-time and taking two courses that I found out were very time-consuming and mostly theoretical and not taught from an application-driven approach. I love to program but the shear amount of effort to switch to Java and learning MIPS Assembly langauge as completly put me off taking any additional course in the MSCS program at JHU. I was hasty in my original plan to leave but I also was navigating uncharted territory in my new career as a Data Scientist. I still stand by my original comments in this post (below) but the best use of my time and my new found appreciation of machine learning and predicitive modeling (mostly gained from work over the past 3 months) is to return to DePaul’s MSPA program as a part-time student and resume my studies. I’m hopeful that the remainder of my coursework is interesting and engaging and I hope to continue documenting my progress and thoughts on the program for those that are interested in Predictive and Data Analytics.

Thanks for taking me back

  • UPDATE on 4/4/16: This post helped me hash out my “feelings” and angst about the specifics of the MSPA program however I still value the structure and knowledge from another Master’s Degree program which has prompted me to officially withdraw from DePaul University and enroll (as a MS provisional Student until my pre-reqs are complete) in the MS in Computer Science program at Johns Hopkins University Engineering for Professionals. I beleive that this program will emphazise some different pedalogical features that will prepare me to be the best Data Scientist I can be, as well as offer more comprehensive course tracks in Data Science, Bioinformatics, and Cybersecurity. I’m excited by this new adventure!

Master of Data Science - fears, regrets and general thoughts

Originally Posted March 28, 2016

TL;DR : I really don’t need to continue my Data Science MS program, since I can confidently learn the material and build my portfolio independently.

I have no idea what I’m doing, but I’m going to try and capture my thoughts and feelings about my experience as a Master of Science Candidate at DePaul University. I’ve come to a fork in the road about my program as documented in tweet-form. Here are the positive notes and acheivements: I’ve boosted my confidence and technical ability in R Programming, python, sql, [insert any other “essential data science skill” promoted by thought leaders, blogs, and rampant language wars posts], I quit my engineering job, completed a Bioinformatics internship, completed an Insurance ‘Data Science’ internship, made great contacts and friends via Twitter, and completed the 2015 Google Summer of Code program for the R Project Organization BUT, I’m finding it hard to see the necessity and worth of continuing on my in my MS program, since I’ve achieved most of those without the direct assitance of my curriculum and advisor.

I researched on a lot Master’s Degree programs for the past year using all of the resources promoted and suggested to those looking to ‘make it in the industry’. All of those resources implied that as a career transitioner (like me!) I would need a MS degree ontop of my “unrelated” but rigourus engineering BS degree to be considered for data science positions. I choose to apply and enroll in the the MSPA program in March 2014 becasue it fit several checkpoints that I was looking for in a graduate program at the time (i.e. online, flexible and interesting choices in curriculum, cost effective, job opportunities/networking). Everything has been going well and I have achieved several personal and professional milestones since last year but I have only utlized my MS program as a proxy for being considered a “student” for the Google Summer of Code program and my Internships. My Master’s program has allowed be to be seen as a “dedicated student” obtaining verifyiable skills in stats, ML, and CS. Most of my acheivements have come from my hard-work and outside interests and not from completing projects in my coursework.

I feel that I was led to believe that only true Data Scientist’s have advanced degrees, are master white-board coders and are fluent in many computer languages. I have self-diagnosed Imposter Syndrome and I’m starting to see that one of the root causes in my self-doubt is from the very thought leaders in the the Data Science community inflating what it means to be an analytics professional and the seemingly singular pathway to get there.

My real axe to grind lays in the structure of the program and what I’m not getting from it, based on the perspective of taking 5 courses (out of 13 courses). I welcome comments and discussion to call me out on this part, but this is my point of view. I would expect to cultivate my data science portfolio and be provided the opportunities to network leading to gainful employment as a “Data Scientist” from any Master’s Degree programs focusing in data science/predictive analytics/data analytics. But instead, I have tacked on additional 17k in student loans and not completed any major projects to add to my portfolio. I take proctored (midterms and finals) exams that “test” my knowledge of coding and concepts but I can’t show those during an interview. I’ve had some interesting homework assignments that I could discuss but don’t tell a full story. I crave interesting challenges and opportunities to expand my skill set and the DePaul University Master of Science in Predictive Analytics program leaves me craving for alternative methods to supplement the curriculum and the desire to withdraw from the program.

P.S.: April Ludgate-Dwqer says it best: