# Data Science (2019 - 2020)

## Policy on Declaration of Major or Minor in Data Science

Students must complete one DS-UA course with a recorded grade of C or better before they can declare a major or minor in Data Science. This policy applies to all NYU students, not just to those matriculated in CAS. For those students interested in data science and computer science, please stay tuned for more curricular information. Students may declare during the declaration period, which is from mid-February to mid-March. To declare, please reach out to cds-undergraduate@nyu.edu for the form or for more information please visit https://cds.nyu.edu/academics/undergraduate-program/.

**Major in Data Science**

The major requires thirteen 4-point courses (52 points) and the completion of any CAS minor (__ completion of minor does not apply to students pursuing joint or double majors__). This minor requirement only applies to students pursuing data science as a single major (not applicable for students pursuing a double major). The major requires:

The following five courses (20 points) sponsored by the NYU Center for Data Science:

- Data Science for Everyone (DS-UA 111)
- Introduction to Data Science (DS-UA 112)
- Causal Inference (DS-UA 201)
- Responsible Data Science (DS-UA 202)
- Advanced Topics in Data Science (DS-UA 301)

The following four courses (16 points) sponsored by NYU's Department of Computer Science (Courant):

- Introduction to Computer Science (CSCI-UA 101)
- Data Structures (CSCI-UA 102)
- Introduction to Machine Learning (CSCI-UA 473)
- Data Management and Analysis (CSCI-UA 480-007)

The following four courses (16 points) sponsored by NYU's Department of Mathematics (Courant):

- Calculus I (MATH-UA 121) or Mathematics for Economics I (MATH-UA 211)
- Calculus II (MATH-UA 122) or Mathematics for Economics II (MATH-UA 212)
- Linear Algebra (MATH-UA 140)
- Probability and Statistics (MATH-UA 235)

Completion of any CAS minor. CAS minors range from four to six courses. This minor requirement only applies to students pursuing data science as a single major (** not applicable for students pursuing a double or joint major**). Please note that due to the substantial overlap with computer science, DS majors cannot minor in computer science.

**Policies Applying to the Major**

- A grade of C or better is necessary in all courses used to fulfill major requirements; courses graded Pass/Fail do not count toward the major.
- Prospective majors must begin the major sequence by taking Data Science for Everyone (DS-UA 111) no later than the first semester of their sophomore year, thus allowing three years to complete the major requirements.
- Two courses may be double-counted between the data science major and another major. For permission to double-count more than two courses, students must petition CAS Academic Standards (Silver 909; 212-998-8140).

- Advanced Placement credit (or other advanced standing credit) in computer science and calculus is treated exactly as in the majors and minors in computer science and mathematics. Consult those departments' sections in this Bulletin, as well as the AP and other tables in the admission section.

- Students must check the prerequisites for each course before enrolling. See the section on course offerings for all prerequisites.
- CAS students (in any major or minor) are not permitted to take computer science courses in the Tandon School of Engineering.
- Those interested in spending a semester away should work out their schedule with an adviser as early as possible.

**Recommended Program of Study for the Major in Data Science**

**Year one fall term:**

- Data Science for Everyone (DS-UA 111)

- Calculus I (MATH-UA 121) or Mathematics for Economics I (MATH-UA 211)
- If required, the prerequisite course Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3). Students who do not need the prerequisite may enroll in Introduction to Computer Science (CSCI-UA 101).

**Year one spring term:**

- Introduction to Data Science (DS-UA 112)

- Calculus II (MATH-UA 122) or Mathematics for Economics II (MATH-UA 212)
- Introduction to Computer Science (CSCI-UA 101)

**Year two fall term:**

- Causal Inference (DS-UA 201)

- Data Structures (CSCI-UA 102)

- Linear Algebra (MATH-UA 140)

**Year two spring term:**

- Probability and Statistics (MATH-UA 235)

- Special Topics: Data Management and Analysis (CSCI-UA 480-007)

**Year three fall term:**

- Introduction to Machine Learning (CSCI-UA 473)

**Year three spring term:**

- Responsible Data Science (DS-UA 202)

- Advanced Topics in Data Science (DS-US 301)

## Minor In Data Science

The minor requires five 4-point courses (20 points). All students in the minor will take these three courses offered by the Center for Data Science:

- Data Science for Everyone (DS-UA 111)
- Introduction to Data Science (DS-UA 112)
- Causal Inference (DS-UA 201)

Students will also take two courses offered by the Department of Computer Science (Courant). Choose one pathway:

**Students entering the minor with no prior programming experience:**

- Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2)
- Either Database Design and Implementation (CSCI-UA 60) or Programming Tools for the Data Scientist (CSCI-UA 381)

**Students entering the minor with limited prior programming experience:**

- Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3)
- Either Database Design and Implementation (CSCI-UA 60) or Programming Tools for the Data Scientist (CSCI-UA 381)

**Students entering the minor with extensive prior programming experience:**

- Database Design and Implementation (CSCI-UA 60)
- Programming Tools for the Data Scientist (CSCI-UA 381)

## Policies Applying to the Minor

- All students who wish to minor in data science must complete a minor registration form, and must consult a minor adviser prior to any registration. Non-CAS students should fill out the minor declaration form via Albert. Please consult the page detailing policies and procedures for cross-school minors.

- A grade of C or better is required in all courses used to fulfill minor requirements (Pass/Fail grades do not count). This policy applies to all NYU students, not just to those matriculated in CAS.
- Students must check the prerequisites for each course before enrolling. See the section on course offerings for all prerequisites.
- Because of the substantial curricular overlap between computer science, data science, and mathematics, students who choose to minor in data science may double-count only one course between the computer science or mathematics major or minor and the data science minor. Students should consult the guidelines of their major for any additional restrictions and policies.
- In accordance with the cross-school minor policy, CAS students may not minor in data science at NYU Shanghai. They may, however, take applicable Shanghai courses and count them toward the CAS data science major or minor.