Congratulations on your acceptance to NYU’s Center for Data Science’s Master of Science in Data Science Program!
Please know that you should be proud of this achievement as careful attention was paid to the composition of our incoming class. We look forward to having you join us this fall, and would like to give you some potentially helpful information and links.
For any other questions or concerns, please contact Kathryn Angeles, Program Administrator, at email@example.com.
- Gearing up for Fall
Get Started Learning Python and the Key Data Science Libraries
If You will Buy a Laptop
- Ross, A first course in probability
- Bertsekas and Tsitsiklis, Introduction to probability
- Casella and Berger, Statistical inference
- Wasserman, All of statistics
- DeGroot and Schervish, Probability and statistics
- Freedman, Pisani and Purves, Statistics
Thinking About Electives
- New Student Orientation and Resources
- New Student Checklist
- Obtaining Your NetID
- GSAS International Student Reference Guide
- Summer Writing Workshop
- Housing and Student Life
- NYU's Office of Global Services (OGS)
- Financial Assistance and Other Frequently Asked Questions About Funding
The Introduction to Data Science and most subsequent other classes will use Python with the libraries matplotlib, numpy, pandas, and scikit-learn. CDS provides a class that will help you get up to speed. It’s called “Programming for Data Science.” You should consider taking it in the fall if you are not confident in your programming skills.
If you don’t know python, go ahead and learn it. A good book to study is McKinney’s “Python for Data Analysis,” which covers numpy, pandas, matplotlib, and iPython.
If you want to start learning the libraries, you should install them and then search for and follow tutorials. The libraries are complicated to install, so we suggest that you use the anaconda package manager to install them. You can install it via www.continuum.io.
Many classes will use iPython. You can install it via anaconda.
You will need a laptop. Some classes require that you bring a laptop to class. Most laptops will be OK.
If you plan to buy a new laptop, consider buying any Apple computer. Apple will give you a small discount if you buy using your NYU email address. Buy the one with as much memory as you can afford. Favor more memory over faster CPUs.
If you end up using a Windows computer, you should install a version of linux in a virtual machine. None of the classes provide code known to work in Windows and many of the classes assume that you can use the Unix command line. (Mac OS is based on BSD Unix and linux is based on Unix, so if you know the command line for one, you mostly know it for the others. The Windows command line is completely different from the Unix command line.)
Windows users should definitely install a linux distribution in a virtual machine. Mac users should as well. Any virtual machine will do, as will any linux distribution. A good choice is VirtualBox for the virtual machine, and the most recent Ubuntu long-term support (LTS) release. Both are free.
If you just finished a statistics degree, you are prepared to take the Statistics and Mathematical Methods class (DS-GA 1002). This fall, the class will focus just on probability and statistics. You may believe that you already know this material and would like to place out of the class. To do that, contact Kathryn Angeles, Program Administrator, at firstname.lastname@example.org.
If statistics is a distant memory, find any undergraduate statistics book and brush up. If you end up buying a book, last year Professor Fernandez-Granda, who will teach the statistics course this fall, recommended these books:
If statistics is completely new to you, you can learn the basics by working through Grus’s “Data Science from Scratch,” which uses Python 3.5 to take an intuitive, computational approach to statistics. This book is also a good not-so-mathy introduction to machine learning.
The degree is designed so that you can take electives that are related to whatever you want to do once you graduate. So figure out your post-graduation interests and take courses appropriately.
You will find a long list of pre-approved courses at http://cds.nyu.edu/academics/pre-approved-elective-courses/. If you find a graduate level course that you want to take and it is not on the pre-approved list, contact Kathryn Angeles, Program Administrator, at email@example.com.
Orientations usually take place in late August/early September, and official invitations are e-mailed to the students during the summer so please look out for this email.
There will be a Graduate School of Arts and Sciences (GSAS) orientation and a separate Center for Data Science MS orientation. Please plan to attend both orientations.
Please visit the NYU Graduate School of Arts and Science (GSAS) website for more information on the following topics:
Unfortunately, on-campus housing is very limited for graduate students. For further information , visit NYU’s Office of Residence Life.
The NYU Student Resource Center advises students regarding how to find off-campus housing. They also organize events such as Welcome Week. Feel free to visit their site and browse! Current MS in Data Science students can also provide on finding off-campus housing. If you would like to connect with a current student, email Kathryn Angeles, Program Administrator, at firstname.lastname@example.org.
If you are an international student, please visit the OGS website or email them with direct inquiries (contact info found on the site) on how to prepare for your arrival to the United States.
For information on funding and opportunities for financing your education, please click here.