Overview
Why Data Science at New York University?New York University (NYU) is renowned for its academic excellence and innovative approach to education. The Data Science programme is highly selective, attracting talented individuals eager to make an impact in the data-driven world. With a strong emphasis on practical skills and theoretical knowledge, NYU prepares its students to meet the demands of a rapidly evolving industry. The university's partnerships with leading organisations provide students with unique opportunities for collaboration and real-world application of their studies. Furthermore, the state-of-the-art facilities and resources available at NYU enhance the learning experience, allowing students to engage with cutting-edge technology and research.
Tuition Fee BreakdownThe tuition fees for the Master of Science in Data Science at NYU are as follows:
- International Students: USD 12,942 per semester
- Domestic Students: USD 12,942 per semester
- Local Students: USD 12,942 per semester
Visit the Fees and Funding section for a breakdown in your local currency.
SyllabusThe curriculum for the M.S. in Data Science consists of 36 credits and offers various pathways for students:
- Industry Concentration: Focuses on specialisation aligned with career goals, including industry-targeted coursework and an internship.
- Biomedical Informatics Track: Involves a biomedicine-based capstone project completed with a mentor from the biomedicine field.
- Data Science Track: Offers three areas of interest:
- Big Data
- Mathematics and Data
- Natural Language Processing
Both full-time and part-time students are required to complete all 36 credits within five years of their enrolment in the programme.
Guaranteed Work ExperienceThe programme includes a Practical Training experience, providing students with hands-on opportunities to apply their knowledge in real-world settings, further enhancing their employability upon graduation.
Careers with Data ScienceGraduates of the M.S. in Data Science programme from NYU are well-equipped to pursue various career paths in diverse sectors such as technology, healthcare, finance, and research. Alumni have found positions in leading organisations, leveraging their skills in data analysis, machine learning, and statistical modelling to drive insights and innovation. Potential job roles include Data Scientist, Data Analyst, Machine Learning Engineer, and Research Scientist, among others. The comprehensive training and industry connections afforded by the programme ensure that graduates are prepared to excel in their chosen fields.
Programme Structure
Courses include:
- Data Science
- Probability and Statistics for Data Science
- Machine Learning
- Big Data
- Capstone Project and Presentation
- Inference and Representation
- Deep Learning
- Natural Language Understanding and Computational Semantics
Key information
Duration
- Full-time
- 24 months
Start dates & application deadlines
- Starting
- Apply before
-
Language
Prepare for Your English Test
AI-powered IELTS feedback. Clear, actionable, and tailored to boost your writing & speaking score. No credit card or upfront payment required.
- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Credits
Delivered
Campus Location
- New York City, United States
Disciplines
Data Science & Big Data View 461 other Masters in Data Science & Big Data in United StatesWhat students do after studying
Academic requirements
English requirements
Prepare for Your English Test
AI-powered IELTS feedback. Clear, actionable, and tailored to boost your writing & speaking score. No credit card or upfront payment required.
- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Other requirements
General requirements
- GRE scores
- TOEFL or IELTS; however, TOEFL is preferred (Required for all applicants whose native language is not English and who have not received a university degree in an English-speaking country)
- Official college transcripts
- Three letters of recommendation (we prefer all letters on letterhead)
- Statement of Academic Purpose
Tuition Fees
-
International Applies to you
Applies to youNon-residents56646 USD / year≈ 56646 USD / year - Out-of-State56646 USD / year≈ 56646 USD / year
-
Domestic
Applies to youIn-State56646 USD / year≈ 56646 USD / year
Living costs
New York City
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Financing
Interested in financing your studies? Find a student loan that works for you.
Get the funding you need to study in the U.S. or Canada - with a process that's fast, simple, and built for international students.
- Flexible loans from US$2,001 to US$100,000
- Fixed interest rates -- no inflation surprises
- No upfront fees or prepayment penalties
- Accepted at 500+ universities across the U.S. & Canada
- 100% online application -- instant conditional offer
- Free visa & career support through our Path2Success program
Funding
In order for us to give you accurate scholarship information, we ask that you please confirm a few details and create an account with us.
Scholarships Information
Below you will find Master's scholarship opportunities for Data Science.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility