## Presentation from October 24, 2019

View Images of Original Slide Presentation

## Agenda

- Welcome from Director of Undergraduate Studies
- CDS and Undergraduate Overview
- Major/Minor Declaration Information
- Q&A

## Welcome and Introduction to CDS

Presented by Andrea Jones-Rooy, Ph.D., Director of Undergraduate Studies

Contact: ajr348@nyu.edu; Office hours: W, 1-3p, CDS #640

## CDS Staff

- Julia Kempe, Director
- Andrea Jones-Rooy, Director of Undergraduate Studies
- Remi Moss, Director of Administration and Operations
- Kathryn Angeles, Director of Academic and Student Affairs
- Emily Mathis Corona, Head of Communications and Manager, Moore-Sloan Data Science Environment
- Timothy Baker, Program Administrator for Academic Affairs and Admissions
- Loraine Nascimento, Head of External Relations and Professional Development
- Aimee-Catherine Zambrana, Administrative Aide II
- Alicia Ocasio, Administrative Aide II

## Overview

- The CDS undergraduate program is designed to equip and empower students of all backgrounds and experience levels to become practitioners of rigorous, thoughtful, and ethical data science.
- Data science is the new language of the 21st century and has become a cornerstone of a liberal arts education.
- As academic disciplines, industries, and media outlets rely more on data-driven decision making, research, and evidence, data science skills are increasingly becoming a requirement for students entering the workforce, government, or research after graduation.
- Data Science empowers us to be sophisticated consumers of data and visualizations and allows us to analyze and generate discoveries.
- It is naturally becoming a prerequisite for being a global citizen, scientist, and leader.

## Major and Minor

- We are pleased to announce our new innovative and interdisciplinary major and minor in Data Science.
- Both programs of study are open to all undergraduate students from across the humanities, social sciences, and sciences, and our courses are open to all students.
- Students who complete the major in data science will be equipped to apply existing data science theories and technologies to problems in many liberal arts domains across the humanities, social sciences, and sciences.
- Students will acquire a thorough knowledge base in computer science and statistics, as well as a deep understanding of current theories, research methodologies, and tools needed to analyze big data, make inferences, explore data-driven decision making, and engage in ethical and privacy considerations.

## Major in Data Science

### Data science major requirements

- Thirteen 4-point courses (52 points)
- 5 courses (20 points) sponsored by the NYU Center for Data Science
- 4 courses (16 points) sponsored by NYU’s Department of Computer Science (Courant)
- 4 courses (16 points) sponsored by NYU’s Department of Mathematics (Courant)

- 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 needed for students pursuing a double major)

### Data Science Courses

- 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)

### Computer Science Courses

- 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 479)

### Mathematics Courses

- 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)

### Policies for Major

- All students who wish to major in data science must complete a major declaration form.
- 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) or Intro to Data Science (DS-UA 112) no later than the first semester of their sophomore year.
- Two courses may be double-counted between the data science major and another major.
- 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.
- 16-credit limit on external NYU (non-CAS) courses that one can take as long as the student is meeting the 64 credit minimum that must be taken at CAS.
- Students must check the prerequisites for each course before enrolling.
- 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. Note some (not all) study away sites offer courses that may count for the major (e.g., NYUSH) 11

### Data science minor requirements

Five 4-point courses (20 points)

- 3 courses (12 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)

- 2 courses (8 points) sponsored by NYU’s Department of Computer Science (Courant)
- Introduction to Computer Programming (CSCI-UA*) *Course number may change depending on programming experience
- Either Database Design and Implementation (CSCI-UA 60) or Programming Tools for the Data Scientist (CSCI-UA 381)

### Policies for 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.
- A grade of C or better is required in all courses used to fulfill minor requirements. (Pass/Fail grades do not count).
- 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.

## Joint Major in Computer and Data Science

The joint major in computer and data science trains students to use data science systems, the automated systems that effectively predict outcomes of interest and that extract insights from increasingly large data set.

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. 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.

### Computer Science Courses

- Introduction to Computer Science (CSCI-UA 101)
- Data Structures (CSCI-UA 102)
- Computer Systems Organization (CSCI-UA 201)
- Basic Algorithms (CSCI-UA 310)
- Introduction to Machine Learning (CSCI-UA 473)
- Data Management and Analysis (CSCI-UA 479)
- Big data elective: choose one (1) of the following:
- Predictive Analytics (CSCI-UA 475)
- Processing Big Data for Analytics Applications (CSCI-UA 476)

- Computer science elective

### Data Science Courses

- 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)

### Mathematics Courses

- 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)
- Discrete Mathematics (MATH-UA 120)
- Linear Algebra (MATH-UA 140)
- Probability and Statistics (MATH-UA 235)

### Keep an eye out for programs and opportunities related to…

- Research opportunities
- Internships
- Careers and career fairs
- Graduate programs
- Tutoring sessions
- Student and community data science events
- Student research fairs
- CDS’s own data science podcast
- Invited speakers
- And more!

## Helpful Links

For additional questions, please email cds-undergraduate@nyu.edu.