CONTACT & FAQ
Frequently Asked Questions
Please email NYU CUSP’s Assistant Director of Admissions, Kristin Feliz, at firstname.lastname@example.org.
All admitted students should respond to our offer of admission by either accepting or declining in the NYU Albert System. Specific directions are outlined in the Next Steps section. You must confirm your enrollment online by the date indicated in your admissions offer and pay a non-refundable deposit of $500 USD.
If you would like to talk to a faculty member, current student, or alumni, please contact Sattik Deb at email@example.com.
For any questions regarding student services, academic advising, academic policies and procedures, or registering for classes, please email Sattik Deb at firstname.lastname@example.org. Please do not contact Sattik with questions regarding your offer of admission or scholarship (if applicable).
While NYU CUSP does not guarantee graduate housing, there are many resources students can take advantage of to find housing both on- and off-campus.
Check out the housing section of CUSP’s guide to living in New York City to learn how you can apply to NYU’s general graduate housing or find an off-campus apartment.
New York University charges tuition and registration fees on a per-unit basis. The tuition rate for the 2019-2020 academic year is $1,872.00 per unit, plus registration and service fees, for a total tuition of $59,604.
* The Board of Trustees of New York University reserves the right to alter tuition and fees.
For more information visit the tuition & financial information section.
For the start of your graduate program at NYU CUSP, your academic advisor will assist you in registering for classes for the first time. During the summer, you will be sent a Fall Semester Planner designed to capture your registration intentions, your elective choice, as well, your am/pm scheduling preferences (where applicable).
Your University ID number (commonly called your “N number”) is the number you are given when your application is processed. You can find it in your acceptance letter or on your Albert account, under Student Center (your NetID needs to already be activated to access Albert). We strongly recommend that you memorize your N number because it will serve as your on-campus identification number. For example, you will need to provide your N number to schedule appointments at the Wasserman Student Career Center, the Health Center, or at the Student Services Center.
Your NetID is your username for all NYU online services, including your NYUHome account, Albert, NYU wi-fi, as well as off-campus access to the New York University Libraries resources. Your NetID is also the prefix for your NYU email address (example: email@example.com). Additionally, you can choose to use it as a username/login at centers on campus, like the Student Career Services and the Campus Writing Center, which have their individual username/password logins.
Once you get your NYU ID Card, you can find both your NetID and your N Number above the barcode on the back of your card.
Your NYU email address is your NetID (a combination of your initials and numbers) @ nyu.edu.
To access your email, you must ensure that you have completed the following steps:
Activate your Net ID
- Go to start.nyu.edu and follow the instructions. Your NetID is your login and username for your NYU email account.
Log in to NYUHome
- Go to home.nyu.edu and enter your NetID and password. Visit the various tabs to familiarize yourself with the layout and information available. Confirm that you have access to your email account.
Check your NYU Email
Your NYUHome account is your virtual NYU command center for all NYU academic and administrative resources. Make sure to familiarize yourself with NYUHome and Albert before classes start; feel free to click around on your own to see what resources are available to you. You can also watch online tutorials to learn how to use the NYU tools found on NYUHome. See examples below:
For additional training and help, sign up for trainings and workshops offered by ITS.
Please take the time to review, verify and update your contact information, which can be found under the “Personal Information” section of the Student Center on NYUHome (you must enter Albert to access your Student Center). Be sure to review and update both your permanent and local addresses.
Please note that all students will be required to have an “NYU Emergency Alert” cellular phone number and emergency contact information on record in order to be eligible to register for classes. In order to avoid a delay in registering, we suggest that you verify this information prior to the start of the registration period.
For more information, visit the Registrar’s page on registration guidelines.
Please review NYU’s Academic Calendar. This calendar includes important class registration deadlines, holidays, and exam testing periods.
Please note that NYU CUSP’s events and academic schedule may differ than the general NYU calendar. Important dates at NYU CUSP will be made known to you as soon as possible.
We send important information about beginning your journey at CUSP to your personal email account. If you are not currently receiving any emails from CUSP or you need to update your preferred email address, please let us know immediately at firstname.lastname@example.org.
Please make sure to add email@example.com to your approved contacts list and check your spam folder for any emails you may have missed.
Yes! There are many free online courses that our students take before the start of the program. If you are looking for a head start before the Urban Computing Skills Lab, we suggest taking a course on the following topics:
- Intro to Data Analysis
- Introduction to Descriptive Statistics
- Introduction to Inferential Statistics
- Introduction to Machine Learning
- Linear Algebra / Math
- Data Camp
- Udemy – Data Science Courses
- Udacity – Data Science Courses
- UC Berkeley – Foundations of Data Science (free to audit)
- Harvard – Algorithms for Big Data
- Caltech – Learning From Data: A Machine Learning Course
- MIT – Introduction to Computer Science and Programming in Python