PhD in Data Science and Analytics - College of Computing and Software Engineering

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
CS 6045 – Advanced Algorithms STAT 7100 – Statistical Methods CS 8267 – Machine Learning STAT 8240 – Data Mining I	STAT 7220 – Experimental Design CS 8265 – Big Data Analytics STAT 7940 or Equivalent – Project STAT 8250 – 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
STAT 7020 – Statistical Computing and Simulation MATH 8030 – Discrete Optimization STAT 7940 or Equivalent – Project STAT Elective (8000 level)	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 Data Science and Analytics.

Year 3

Fall	Spring
DS 9700 - Data Science Doctoral Applied Research Lab (3 hours) IT/STAT/MATH Electives (8000 level) (9 credit hours)	DS 9700 - 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
DS 9700 – Data Science Doctoral Applied Research Lab DS 9900 – Data Science Doctoral Dissertation	DS 9700 – Data Science Doctoral Applied Research Lab DS 9900 – Data Science Doctoral Dissertation
After completion of Year Four, students will defend a dissertation proposal.

Year 5

Fall

Spring

DS 9700 - Data Science Doctoral Applied Research Lab
DS 9900 – Data Science Doctoral Dissertation

DS 9700 - Data Science Doctoral Applied Research Lab
DS 9900 – 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
CS 6045 – Advanced Algorithms CS 6041 – Theory of Computation CS 8267 – Machine Learning STAT 8240 – Data Mining I	CS 8265 – Big Data Analytics CS Elective (6000 or 7000 level) STAT 8250 – 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) MATH 8030 - Discrete Optimization	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.

Year 3

Column Title 1	Column Title 2
DS 9700 - Data Science Doctoral Applied Research Lab (3 hours) CS Electives (8000 level) (6 credit hours)	DS 9700 - 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
DS 9700 - Data Science Doctoral Applied Research Lab DS 9900 – Data Science Doctoral Dissertation	DS 9700 - Data Science Doctoral Applied Research Lab DS 9900 – Data Science Doctoral Dissertation
After completion of Year Four, students will defend a dissertation proposal.

Year 5

Column Title 1

Column Title 2

DS 9700 - Data Science Doctoral Applied Research Lab
DS 9900 – Data Science Doctoral Dissertation

DS 9700 - Data Science Doctoral Applied Research Lab
DS 9900 – 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.