Kelsey Clubb is currently pursuing a Master of Information and Data Science from the UC Berkeley School of Information and will graduate with the first cohort in August 2015. She will also join the Data Science team at Tesla Motors as an intern in Palo Alto this summer. Kelsey resides in the San Francisco Bay Area, and you can connect with her on twitter @Kelsey_Clubb or LinkedIn.
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One big advantage of the MIDS program was that I could keep my job while I pursued my degree (the majority of students have full-time jobs while completing the program and the instructors are understanding about this), that way, if it didn’t work out for some reason, I wouldn’t have completely uprooted my current path. Other things I liked were that I could complete the program in less than two years (at half-time student status) and that I would have earned a Master’s Degree from UC Berkeley. In the future, degrees from prestigious higher educational institutions might not be worth as much to employers, but I thought it would be an advantage for me personally at this point in time.
The financial cost of the MIDS program was significantly greater than other programs and I was part of the first cohort, so there were no student experiences to consider and certainly no guarantee that employers would look positively upon achieving this degree. Once I was accepted, these factors did cause me some hesitation, but I (obviously) decided it was worth the risk to enroll and I definitely don’t regret my decision.
The biggest challenge I personally faced with learning in a virtual classroom had to do with distractions. In a traditional classroom (in my experience at least), all of the students face the professor while he or she teaches at the front of the class. In our online learning environment, there is such a small class size (~15 students per section) that everyone (teachers and students) has a webcam turned on themselves that everyone else can see during the entire class–in the beginning we likened it to being in the Brady Bunch intro or Hollywood Squares. It can be a bit distracting to see everyone when they move around, and it definitely made me self-conscious at first to know so many eyes were on me, but I’ve actually grown accustomed to it and enjoy being able to see my classmates (at least in two dimensions) each week. I think this is also one of several advantages of this kind of online learning environment compared to a Massive Open Online Course (MOOC) where you primarily only interact with instructors and myriad other students via discussion forums, if at all (which certainly has it’s place, but not for graduate-level degree programs, in my opinion). I feel very connected to my instructors and classmates in the MIDS program.
If you do enroll in a Master’s program, make sure you do projects so that you have work to show and discuss with potential employers. Supplementing your learning with (free) MOOCs can be helpful (but not all MOOCs are good quality). I personally highly recommend Coursera’s Data Analysis and Statistical Inference (Duke), Udacity’s Intro to Machine Learning and Intro to Hadoop and MapReduce, and EdX’s The Analytics Edge (MIT) and Sabermetrics 101: Introduction to Baseball Analytics (Boston University). If you don’t have any industry experience and you’re looking to switch careers (as I was), getting a data science-related internship might facilitate your transition into industry.