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    IIT College of Science Professional Master's Program: Data Science - Rethinking Data

    Program requirements

    The Master of Data Science (MAS DS) is a professional master's degree jointly offered by the Department of Computer Science and the Department of Applied Mathematics. In order to earn a degree, the student needs to complete a total of 33 credits of coursework including a 6-credit summer practicum. A thesis is not required.

    Applicants are evaluated on an individual basis, but are expected to have basic knowledge of discrete mathematics, linear algebra, probability, statistics, relational databases, and some programming such as Matlab, C++, Java, Python, or Ruby.

    Applicants lacking prerequisite coursework but who are otherwise strong candidates (e.g., with relevant work experience) may be admitted, but will be required to make up any needed coursework. In most cases proficiency testing is available to fulfill such prerequisite requirements.

    For all academic questions please contact:

    Program Director
    Shlomo Argamon, Ph.D.
    Department of Computer Science
    312.567.5289
    argamon@iit.edu

    Program Assistant Director
    Lulu Kang, Ph.D.
    Department of Applied Mathematics
    312.567.5322
    lkang2@iit.edu

    Core Coursework:

    All MAS DS students must complete 6 core courses (18 credits) as follows:

    Statistics (one of):

    Machine Learning (one of):

    Data Processing (one of):

    Working with Data:

    Communication (one of):

    Project Management (one of):

    All students are also required to attend at least one semester of the one credit CSP/MATH 570 DATA SCIENCE SEMINAR.

    Data Science Practicum:

    Students are required to take CSP/MATH 572 DATA SCIENCE PRACTICUM (6 credits) in which they will work in small groups to solve real-world data analysis problems for actual scientific or industrial clients. Innovation and clarity of presentation will be key elements of evaluation. Students also have an option to fulfill course requirements through an approved data analytics internship.

    Electives:

    MAS DS students may choose their 3 elective courses (9 credits) from the following list:

    Computation Fundamentals:

    Computer Science Applications:

    Mathematics, Probability and Statistics:

    Mathematical and Scientific Computing:

    Other relevant 500-level coursework may be taken for elective credit, with approval of the program directors.

    Other Requirements:

    Students must take a total of at least 9 credits of CS/CSP coursework and at least 9 credits of MATH coursework to graduate, not including the capstone practicum course. Prerequisite courses MATH 474, CS 401, and CS 402, if taken, will not count towards degrees fulfillment.


    Example Course Schedules:

    FULL-TIME SCHEDULE, FALL START
    Year Fall (12 credits) Spring (15 credits) Summer (6 Credits)
    1 SCI 522
    CS 525 or 554
    MATH 564
    CS 584 or MATH 569
    CSP/MATH 570
    CSP/MATH 571
    CS 587
    3 Electives
    CSP/MATH 572


    FULL-TIME SCHEDULE, SPRING START
    Year Spring (12 credits) Summer (6 credits) Fall (15 Credits)
    1 CS 525 or 554
    CSP/MATH 571
    CS 584 or MATH 569
    1 Elective
    CSP/MATH 570
    CSP/MATH 572 CS 587
    SCI 522
    MATH 564
    2 Electives


    PART-TIME SCHEDULE
    Year Fall (6 credits) Spring (6 credits) Summer (6/3 Credits)
    1 CS 525 or 554
    MATH 564
    CSP/MATH 570
    CS 584 or MATH 569
    CSP/MATH 571
    CSP/MATH 572
    2 SCI 522
    CS 587
    2 Electives 1 Elective


    EXTENDED 16 MONTH SCHEDULE
    Year Fall (9 credits) Spring (9 credits) Summer (6 Credits)
    1 SCI 522
    CS 525 or 554
    MATH 564
    CSP/MATH 570
    CS 584 or MATH 569
    CSP/MATH 571
    CSP/MATH 572
    2 3 Electives

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