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    Data Science

    Data Science at NYU Shanghai is designed to create data-driven leaders with a global perspective, a broad education, and the capacity to think creatively. Data science involves using computerized methods to analyze massive amounts of data and to extract knowledge from them. Data science addresses a wide-range of data types, including scientific and economic numerical data, textual data, and image and video data. This new discipline draws from methodologies and tools in several well established fields, including computer science, statistics, applied mathematics, and economics. Data science has applications in just about every academic discipline, including sociology, political science, digital humanities, linguistics, finance, marketing, urban informatics, medical informatics, genomics, image content analysis, and all branches of engineering and the physical sciences.  The importance of data science is expected to accelerate in the coming years, as data from the web, mobile sensors, smartphones, and Internet-connected instruments continues to grow.

    Students who complete the major will not only have expertise in computer programming, statistics, and data mining, but also know how to combine these tools to solve contemporary problems in a discipline of their choice, including the social science, physical science, and engineering disciplines. Upon graduation, data science majors have numerous career paths. You can  go on to graduate school in data science, computer science, social science, business, finance, medicine, law, linguistics, education, and so on. Outside of academe, there are also myriad career paths. Not only can you pursue careers with traditional data-driven computer-science companies and startups such as Google, Facebook, Amazon, and Microsoft, but also with companies in the transportation, energy, medical, and financial sectors. You can also pursue careers in the public sector, including urban planning, law enforcement, and education.

    Degree Requirements – 2018-19 Bulletin

    * = offered in Fall?’19?in Shanghai

    Prerequisite Courses
    CSCI-SHU 101 Introduction to Computer Science* Pre-req: ICP or placement exam
    Choose one Statistics course from the following four
    MATH-SHU 235 Probability and Statistics* Pre-req: Calculus
    MATH-SHU 233 Honors Theory of Probability* Pre-reqs: “Honors Analysis 1” and “Linear Algebra or Honors Linear Algebra 1”?
    BUSF-SHU 101 Statistics for Business and Economics* ?
    BIOL-SHU 42 Biostatistics ?

    Note: SOCS-SHU 210 Statistics for the Behavioral Sciences does?not?count towards this requirement.

    Programming/Computer Science Courses
    CSCI-SHU 210 Data Structures* Pre-req: ICS, or?A- and above in?ICP
    Math Courses
    MATH-SHU 123? Multivariable Calculus*?
    MATH-SHU 140 OR?MATH-SHU 265 OR MATH-SHU 141 Linear Algebra* OR Linear Algebra and Differential Equations* OR Honors Linear Algebra I*
    Data Analysis Courses

    ECON-SHU 301 OR

    MATH-SHU 234

    Econometrics*?OR

    The Mathematics of Statistics and Data Science, Part 1*

    Pre-req: a?prior Stats course

    Pre-reqs:?Multivariable Calculus, Linear Algebra, and a?prior Stats course

    CSCI-SHU 360 Machine Learning* Pre-reqs:?ICP?and Calculus/Honors Calculus

    CSCI-SHU?235 OR??

    CSCI-SHU 220 OR??

    CSCI-SHU 240

    Information Visualization OR?Algorithms?OR?Introduction to Optimization and Mathematical Programming

    Pre-req: Data Structures

    Pre-req: Calculus, Discrete Math and Data Structures

    Pre-req: ICP; AND Calculus or Honor Calculus ; AND Prob and Stats or Stats for Bus and Econ or Theory of Probability?

    Data Management Course
    CSCI-SHU 213 / CS-UY 3083 Databases* Pre-req: Data Structure
    Concentration Courses
    Domain-area?courses
    Data Science Capstone

    ?

    Concentration Options
    Domain-Area Courses for Concentration in Finance
    ? Data Science Capstone (Not Required for students who are enrolled in 6-credit Business and Econ Honors Program)
    ECON-SHU 3 Microeconomics*
    BUSF-SHU 250 Principles of Financial Accounting*
    BUSF-SHU 202 Foundations of Finance*
    BUSF-SHU 303 Corporate Finance*

    14 courses total.

    Domain-Area Courses for Concentration in Marketing
    ? Data Science Capstone (Not Required for students who are enrolled in 6-credit Business and Econ Honors Program)
    ECON-SHU 3 Microeconomics*
    BUSF-SHU 250 Principles of Financial Accounting*
    BUSF-SHU 202 Foundations of Finance*
    MKTG-SHU 1 Introduction to Marketing*

    14 courses total.

    Domain-Area Courses for Concentration in Economics
    ? Data Science Capstone (Not Required for students who are enrolled in 6-credit Business and Econ Honors Program)
    ECON-SHU 3 Microeconomics*
    ECON-SHU 1 Principles of Macroeconomics*

    12 courses total.

    Domain-Area Courses for Concentration in Genomics
    ? Data Science Capstone
    BIOL-SHU 21 Foundations of?Biology 1 and lab
    BIOL-SHU 22 Foundations of Biology 2 and lab*
    BIOL-SHU 261 Genomics and Bioinformatics*

    Foundations of?Biology 1 can count as core curriculum course.

    12 courses total.

    Domain-Area Courses for Concentration in Computer Science
    ? Data Science Capstone
    Two courses from:
    CENG-SHU 202 OR?CSCI-UA 201 Computer Architecture?OR Computer Systems Organization
    CSCI-SHU 215 Operating Systems*
    CSCI-SHU 2314 Discrete Mathematics*
    CS-UY 2413 / CSCI-UA 310 / CSCI-SHU 220 Algorithms

    12 courses total.

    Domain-Area Courses for Concentration in Mathematics
    ? Data Science Capstone
    Two courses from: ?
    MATH-SHU 201 Honors Calculus*
    MATH-SHU 233 Honors Theory of Probability*
    MATH-SHU 234 The mathematics of Statistics and Data Science*
    MATH-SHU 142 Honors Linear Algebra 2
    MATH-SHU 329(203) Honors Analysis II (Analysis II)*

    12 courses total.

    Domain-Area Courses for Concentration in Artificial Intelligence
    ? Data Science Capstone
    Two courses from:
    CSCI-UA 480 Natural Language Processing
    CSCI-SHU 372 / CS-UY 4613 Artificial Intelligence
    CSCI-GA 2566? Foundations of Machine Learning
    DS-GA 1008 /?CSCI-GA?2572 Deep Learning
    DS-GA 1012 Natural Language Understanding and Computational Semantics
    DS-GA 1013 Mathematical Tools for Data Science
    DS-GA? 3001 Probabilistic Times Series Analysis
    CSCI-SHU?240 Introduction to Optimization and Mathematical Programming
    CSCI-SHU 235 Information Visualization
    CS-UY 2413 / CSCI-UA 310 / CSCI-SHU 220 Algorithms
    CSCI-SHU 375 Reinforcement Learning

    12 courses total.

    Domain-Area Courses for Concentration in Political Science
    ? Data Science Capstone
    SOCS-SHU 150 Introduction to Comparative Politics
    SOCS-SHU 160 Introduction to International Politics*


    12 courses total.

    Domain-Area Courses for Concentration in Psychology
    ? Data Science Capstone?
    Two Required Courses:
    SOCS-SHU 350 Empirical Research Practice*
    SOCS-SHU 101 Introduction to Psychology*
    One course from:
    PSYC-SHU 234 Developmental Psychology
    PSYCH-UA 25 Cognitive Neuroscience
    PSYCH-UA 32 Social Psychology
    PSYCH-UA 30 Personality
    PSYCH-SHU 352?OR PSYCH‐UA 300 Psychology of Human Sexuality*?OR Human Sexuality
    SOCS-SHU 334 Legal Psychology

    13?courses total.

    Double Majors

    If you are interested in pursuing a Data Science major along with an Economics major, a Computer Science major, a Business major, or a Mathematics major, these are the relevant guidelines:

    • The course requirements need to be satisfied in?both majors.
    • More than two courses may be double-counted between the majors but each major must have?at least?7 singly-counted courses.
    • The double major must be approved by the faculty and Deans responsible for the two majors. Students should first work with their academic advisor to initiate this process.
    • Double-counted courses cannot also be counted for the core curriculum requirements since each course can only count for at most two requirements.

    ?

    You can view sample plans on how a major in Data Science and an Economics major, a Computer Science major, a Business major, or a Mathematics major may be completed?HERE.

    Recommended Fall 2019 Courses

    Recommended Fall?2019?Courses

    1. Introduction to Computer Science
    2. Data Structures
    3. Machine Learning
    4. Databases
    5. Econometrics
    6. The Mathematics of Statistics and Data Science
    Faculty Mentors

    Prof. Keith Ross, Dean of Engineering and Computer Science?Office: 1415 | Email:?kwr200@nyu.edu?|?Profile

    ?

    Prof. Yuxin Chen, Dean of Business?Office: 1124 | Email:?yc18@nyu.edu?|?Profile

    Minor in Data Science: 5 courses
    CSCI-SHU 101 Introduction to Computer Science*
    CSCI-SHU 210 Data Structures*

    ECON-SHU 301?OR

    MATH-SHU 234

    Econometrics*?OR

    The Mathematics of Statistics and Data Science*

    CSCI-SHU 360 Machine Learning*
    One Statistics course from the following four
    MATH-SHU 235 Probability and Statistics*
    BUSF-SHU 101 Statistics for Business and Economics*
    MATH-SHU 233 Honors Theory of Probability*
    BIOL-SHU 42 Biostatistics
    Note: Computer Science majors should additionally take Information Visualization OR Databases to earn at least 12 unique credits for the minor.
    Undergraduate Research
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