Embedded Pathways to a Ph.D.

Collage of four images showing embedded pathways students in classroom, labs, and community events.

Applicants* who want to be considered for the PhD in Data Science and Analytics 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 Data Science and Analytics.

Ph.D. with (MSDSA) Embedded

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

Year 1

Fall Spring
  •  â€“ Advanced Algorithms
  •  â€“ Statistical Methods
  •  â€“ Machine Learning
  •  â€“ Data Mining I
  •  â€“ Experimental Design
  •  â€“ Big Data Analytics
  •  or Equivalent –  Project
  • – Data Mining II

After completion of Year One, students will take a Data Science Qualifying Exam for consideration to be accepted into the PhD in Data Science and Analytics Program. A separate application to the PhD program should be submitted by the Feb. 1 deadline. Please make sure to check the admission requirements as they are different from the MS program. 

Year 2

Fall Spring
  •  â€“ Statistical Computing
    and Simulation
  • – Discrete Optimization
  •  or Equivalent –  Project
  • STAT Elective (8000 level)
  • STAT Elective (8000 level)
  • – 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 Data Science and Analytics.

Year 3

Fall Spring
  •  - Data Science Doctoral Applied Research Lab (3 hours)
  • IT/STAT/MATH Electives (8000 level)
    (9 credit hours)
  •  - Data Science Doctoral Applied Research Lab (3 hours)
  • IT/STAT/MATH Electives (8000 level) (6 credit hours)
After completion of Year Three, students will prepare and present a formal research proposal.

Year 4

Fall Spring
  •  â€“ Data Science Doctoral Applied Research Lab
  •  â€“ Data Science Doctoral Dissertation 
  •  â€“ Data Science Doctoral Applied Research Lab
  •  â€“ Data Science Doctoral Dissertation 
After completion of Year Four, students will defend a dissertation proposal.  

Year 5

Fall Spring
  •  - Data Science Doctoral Applied Research Lab
  •  â€“ Data Science Doctoral Dissertation 
  •  - Data Science Doctoral Applied Research Lab
  •  â€“ Data Science Doctoral Dissertation

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.

Ph.D. with (MSCS) Embedded

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

Year 1

Fall Spring
  •  â€“ Advanced Algorithms
  •  â€“ Theory of Computation
  • – Machine Learning
  •  â€“ Data Mining I
  •  â€“ Big Data Analytics
  • CS Elective (6000 or 7000 level)
  •  â€“ Data Mining II
After completion of Year One, students will take a Data Science Qualifying Exam for consideration to be accepted into the PhD in Data Science and Analytics Program. A separate application to the PhD program should be submitted by the Feb. 1 deadline. Please make sure to check the admission requirements as they are different than the MS program. 

Year 2

Column Title 1 Column Title 2
  • 2 CS Electives (6000 or 7000 level)
  •  - Discrete Optimization
  • CS Elective (8000 level)
  •  â€“ Graph Theory
  •  â€“ Data Science Applied Project
After completion of Year Two, students are expected to have completed the requirements for the MS in Computer Science.

Year 3

Column Title 1 Column Title 2
  •  - Data Science Doctoral Applied Research Lab (3 hours)
  • CS Electives (8000 level) (6 credit hours)
  •  - Data Science Doctoral Applied Research Lab (3 hours)
  • CS Electives (8000 level) (6 credit hours)
After completion of Year Three, students will prepare and present a formal research proposal.

Year 4

Fall Spring
  •  - Data Science Doctoral Applied Research Lab
  •  â€“ Data Science Doctoral Dissertation 
  •  - Data Science Doctoral Applied Research Lab
  •  â€“ Data Science Doctoral Dissertation 
After completion of Year Four, students will defend a dissertation proposal.

Year 5

Column Title 1 Column Title 2
  •  - Data Science Doctoral Applied Research Lab
  •  â€“ Data Science Doctoral Dissertation 
  •  - Data Science Doctoral Applied Research Lab
  •  â€“ Data Science Doctoral Dissertation

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.