Overview
The Computer and Data Science programme from New York University trains students to use data science systems, the automated systems that effectively predict outcomes of interest and that extract insights from increasingly large data sets. This training enables students to participate in harnessing the power of data and in influencing policies that will govern the rollout of data science technologies.
Key facts
- In addition, students gain the ability to build such systems. This is an interdisciplinary major (eighteen courses/72 points) offered by the Department of Computer Science and the Center for Data Science. A grade of C or better is necessary in all courses used to fulfill joint major requirements.
- Interested students should consult with the directors of undergraduate studies in the department and the center for additional information.
- Please note that the CAS minor requirement associated with the major in data science is waived for the computer and data science joint major, just as it is waived for a data science major pursuing a double major.
Learning Outcomes
Upon completion of programme requirements, students are expected to have developed:- Fundamental theoretical and practical knowledge of the foundational areas of computer science, including algorithm design, machine learning, and programming.
- Knowledge of current methods and tools used to analyze big data and inferences, and to explore data-driven decision making.
- Knowledge of ethical issues regarding data science. These include the topics of fairness, diversity, and privacy.
- The ability to build and use data science systems, the automated systems that effectively predict outcomes of interest and that extract insights from increasingly large data sets.
- An understanding of what is going on "under the hood" of computer software in terms of the underlying computer architecture and operating systems.
Programme Structure
Courses include:
- Data Structures
- Computer Systems Org
- Predictive Analytics
- Processing Big Data for Analytics Applications
- Data Management and Analysis
- Causal Inference
- Responsible Data Science
Key information
Duration
- Full-time
- 48 months
Start dates & application deadlines
- Starting
- Apply before
-
Language
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Credits
Delivered
Campus Location
- New York City, United States
Disciplines
Computer Sciences Data Science & Big Data View 460 other Bachelors in Data Science & Big Data in United StatesWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
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- 98 accuracy using real exam data
- 4.9/5 student rating
Other requirements
General requirements
- Standardized test scores (see NYU’s standardized testing requirements). Standardized testing is optional for the upcoming application term.
- A Self Reported Academic Record (SRAR). All applicants will be invited to complete this after submitting their application.
- English language testing if you have not completed at least 3 years of study where English is the sole language of instruction at the time of application submission and English is not your first language.
- Records of all college work that you have received academic credit for and does not appear on your high school transcript.
- The Common Application Mid Year Report with updated academic record if mid-year grades are available. This should show your first semester senior year grades.
Tuition Fees
-
International Applies to you
Applies to youNon-residents65622 USD / year≈ 65622 USD / year - Out-of-State65622 USD / year≈ 65622 USD / year
-
Domestic
Applies to youIn-State65622 USD / year≈ 65622 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.
Funding
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Scholarships Information
Below you will find Bachelor's scholarship opportunities for Computer and Data Science.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
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