Embedded Pathways to a Ph.D.

Embedded Pathway to a PhD Header

Applicants* who want to be considered for the PhD in Analytics and Data Science without a Masters degree (but have completed a quantitative Bachelor’s degree) can apply to the embedded MS in Computer Science or the embedded MS in Applied Statistics and Analytics.

Ph.D. with (MSAS) Embedded

Curriculum for the PhD in Analytics and Data Science with an embedded MS in Applied Statistics (all courses are 3 credit hours unless otherwise specified):

Ph.D. with (MSCS) Embedded

Curriculum for the PhD in Analytics and Data Science with an embedded MS in Computer Science (all courses are 3 credit hours unless otherwise specified):

MSAS Year One (Fall)

MSAS Year One (Spring)

After completion of Year One, students will take a Data Science Qualifying Exam for consideration to be accepted into the PhD in Analytics and Data Science Program.

MSCS Year One (Fall)

MSCS Year One (Spring)

  • CS 8265 – Big Data Analytics
  • CS Elective (6000 or 7000 level)
  • STAT 8250 – Data Mining 2

After completion of Year One, students will take a Data Science Qualifying Exam for consideration to be accepted into the PhD in Analytics and Data Science Program.

MSAS Year Two (Fall)

  • STAT 7020 – Statistical Computing
    and Simulation
  • MATH 8030 – Discrete Optimization
  • STAT 8940 – Applied Statistics Project
  • STAT Elective (8000 level)

MSAS Year Two (Spring)

  • STAT Elective (8000 level)
  • MATH 8020 – Graph Theory
  • STAT/DS Elective (8000 level)
    (6 credit hours)

After completion of Year Two, students are expected to have completed the requirements for the MS in Applied Statistics and Analytics.

MSCS Year Two (Fall)

  • 2 CS Electives (6000 or 7000 level)
  • MATH 8030 - Discrete Optimization
     

MSCS Year Two (Spring)

  • CS Elective (8000 level)
  • MATH 8020 – Graph Theory
  • DS 7900 – Data Science Applied Project

After completion of Year Two, students are expected to have completed the requirements for the MS in Computer Science.




MSAS Year Three (Fall)

  • IT/STAT/MATH Electives (8000 level)
    (12 credit hours)

MSAS Year Three (Spring)

  • IT/STAT/MATH Electives (8000 level) (9 credit hours)

After completion of Year Three, students will prepare and present a formal research proposal.

MSCS Year Three (Fall)

  • CS Electives (8000 level) (9 credit hours)

MSCS Year Three (Spring)

  • CS Electives (8000 level) (9 credit hours)

After completion of Year Three, students will prepare and present a formal research proposal.

MSAS Year Four (Fall)

  • DS 9700 – Data Science Doctoral Applied Research Lab
  • DS 9900 – Data Science Doctoral Dissertation (9 credit hours)

MSAS Year Four (Spring)

  • DS 9700 – Data Science Doctoral Applied Research Lab
  • DS 9900 – Data Science Doctoral Dissertation (9 credit hours)

After completion of Year Four, students will defend a dissertation proposal.

MSCS Year Four (Fall)

  • DS 9900 – Data Science Doctoral Dissertation (9 credit hours)

MSCS Year Four (Spring)

  • DS 9900 – Data Science Doctoral Dissertation (9 credit hours)

After completion of Year Four, students will defend a dissertation proposal.




MSAS Year Five (Fall)

  • DS 9900 – Data Science Doctoral Dissertation (9 credit hours)

MSAS Year Five (Spring)

  • DS 9900 – Data Science Doctoral Dissertation (6 credit hours)

After completion of Year Five, students will defend a final dissertation.

 *Students with no previous CS training will be required to complete the Foundations in CS (MOOC version of CS5040) for no credit hours in the preceding summer.  Students with no previous STAT degrees will have to complete STAT7010 and STAT8/7210 for credit hours in the preceding summer.

MSCS Year Five (Fall)

  • DS 9900 – Data Science Doctoral Dissertation (9 credit hours)

MSCS Year Five (Spring)

  • DS 9900 – Data Science Doctoral Dissertation (6 credit hours)

After completion of Year Five, students will defend a final dissertation.

* Students with no previous CS training will be required to complete a Foundations in Computer Science course (MOOC version of CS5040) for no credit hours in the preceding summer.  Students with no previous STAT degrees will have to complete STAT7010 and STAT8/7210 for credit hours in the preceding summer.

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