2013 Data Science Focus Course Planning Worksheet Final

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QMSS Data Science Focus Course Planning Worksheet, AY 2013-2014 Name: ___________________________________ UNI: _______________________________________ Entered Program: _________________________ Expected Graduation: ________________________ Full-time students are expected to complete the program in 2 semesters of coursework. Part-time students are expected to complete the program in 4-5 semesters of coursework. If you want to spend additional time at Columbia, please contact QMSS program staff to discuss your academic plan. Thirty (30) points minimum are required for the degree. Students must maintain a 3.0 or above average. Course Requirements Points Semester/Year A. QMSS G4010: Theory and Methodology 4 Fall B. QMSS G4021: Research Seminar 2 Fall QMSS G4022: Research Seminar 2 Spring C. Data Analysis: fulfilled by one of the following a. Probability and Statistics (STAT W4700) 3 Fall b. Multivariate Political Analysis (POLS W4912) 3 Fall c. Data Analysis for the Social Sciences (QMSS G4015) 4 Fall D. Introduction to Data Science (STAT W4242) 3 Fall E. Practical Data Science: take one of the following a. Computational Social Science (APMA E4990) 3 Spring b. Applied Data Science (STAT W4249) 3 Spring F. Algorithmic Learning: take one of the following 3 Spring a. Statistical Machine Learning (STAT W4400) 3 Fall/Spring b. Machine Learning (COMS W4771) 3 Fall/Spring c. Data Mining (STAT W4240) 3 Spring d. Applied Data Mining (STAT W4026) 3 Fall G. Data Visualization (QMSS G4063) 4 Fall/Spring H. Elective course I. Elective course J. QMSS G5999: Master’s Thesis 3 or 4 Thesis Title: ______________________________________________________________________________________ Advisor (if applicable): _____________________________________________________________________________

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2013 Data Science Focus Course Planning Worksheet Final

Transcript of 2013 Data Science Focus Course Planning Worksheet Final

  • QMSS Data Science Focus Course Planning Worksheet, AY 2013-2014

    Name: ___________________________________ UNI: _______________________________________

    Entered Program: _________________________ Expected Graduation: ________________________

    Full-time students are expected to complete the program in 2 semesters of coursework. Part-time students are expected to complete the program in 4-5 semesters of coursework. If you want to spend additional time at Columbia, please contact QMSS program staff to discuss your academic plan. Thirty (30) points minimum are required for the degree. Students must maintain a 3.0 or above average. Course Requirements Points Semester/Year

    A. QMSS G4010: Theory and Methodology 4 Fall

    B. QMSS G4021: Research Seminar 2 Fall

    QMSS G4022: Research Seminar 2 Spring

    C. Data Analysis: fulfilled by one of the following

    a. Probability and Statistics (STAT W4700) 3 Fall

    b. Multivariate Political Analysis (POLS W4912) 3 Fall

    c. Data Analysis for the Social Sciences (QMSS G4015) 4 Fall

    D. Introduction to Data Science (STAT W4242) 3 Fall

    E. Practical Data Science: take one of the following

    a. Computational Social Science (APMA E4990) 3 Spring

    b. Applied Data Science (STAT W4249) 3 Spring

    F. Algorithmic Learning: take one of the following 3 Spring

    a. Statistical Machine Learning (STAT W4400) 3 Fall/Spring

    b. Machine Learning (COMS W4771) 3 Fall/Spring

    c. Data Mining (STAT W4240) 3 Spring

    d. Applied Data Mining (STAT W4026) 3 Fall

    G. Data Visualization (QMSS G4063) 4 Fall/Spring

    H. Elective course

    I. Elective course

    J. QMSS G5999: Masters Thesis 3 or 4

    Thesis Title: ______________________________________________________________________________________

    Advisor (if applicable): _____________________________________________________________________________

    QMSS Data Science FocusCourse Planning Worksheet, AY 2013-2014Thesis Title: ______________________________________________________________________________________Advisor (if applicable): _____________________________________________________________________________