How good is Columbia Data Science MS program?
There are a decent number of Data Science programs in the US and their count is increasing every year. We are going to review how good Columbia Data Science program is in this post. We base it on the effectiveness of the curriculum, job opportunities and cost of attending. And then, in the end, we make our recommendation whether someone should attend this program or not. Here, we go-
It is a 30 credit course (10×3) with 7 core and 3 elective courses and 1 capstone project. Core courses include Machine Learning, Visualization, Statistics and Inference Modeling. Elective courses can be taken from any department (Journalism, CS, business school, ECE). For example, cloud computing and analytics, Big data, building story from data etc. It is a 1.5 years course (or can be completed in 1 year but not recommended). The curriculum is good and challenging. TA’s conduct special training sessions on Python and R whenever required for a course. One is expected to have a good understanding of Statistics and Linear Algebra. We feel that curriculum designed for an overall exposure and can give a good platform to begin your Data Science journey.
Being an Ivy league brand, expect good career services office and resources to help you find a good career opportunity. Data Science is a separate department and it holds a separate career fair only for DS students, which is a big plus. Additionally, Columbia career fair is open to all. Apart from this, the program benefits a lot from its location as there are multiple startup job fairs in NYC which are all a subway ride away. Arushi, despite being a fresher, managed offers from Amazon, Milliman Max, and Synergic Partners (Madrid). Everyone got an internship in 2016.
Cost of attending
This is where Columbia hurts. With around $56,000 in tuition alone and $1800 per mon of living costs, program is one of the costliest in the US. There are practically no scholarships and on-campus jobs pay very little ($9-12 per hour) and so does TAships ($2500 per sem).
Location and Brand are a big plus and give you unlimited opportunities at networking and exposure. With average GPA of 3.5 and GRE score of 319+, the admission is very competitive. The program encourages freshers as well as non-CS grads to apply, therefore class is overall diverse in background.
Biggest competitors are CMU BIDA, CMU MCDS, UT Austin MSBA, U Washington, Georgia Tech etc. While CMU is still the touted leader, Columbia Data Science is catching up fast.
So, given all the factors, we feel that Columbia Data Science program is defintely worth attending if one can manage the finances. We give it a rating of 4/5 hats!
Which program do you want to know about next? Join our FB group and tell us!
Above information is based on our webinar series where our 2015 student Arushi Arora shared her views and lot of useful information about Columbia and recruitment in Data Science in general. A big thanks to her!
In the same webinar series, next session is by Vivek Joshi, Marketing Data Scientist at Hertz where he will share his experiences about studying Analytics in USA! Dont miss it, for more details head over to our Facebook group on MS internships by clicking here.
If you want to work with us on your applications, look at our mentorship packages. Good luck 🙂