PhD Computer Science, Data Science and Analytics Concentration - Degree Requirements

MS to PhD

A minimum of 72 graduate credits is required beyond a bachelor's degree. A master's degree in a related field is considered equivalent to 30 credits. A minimum of 18 credits of coursework is required beyond a master's degree. All courses must be approved by the student's advisor. In addition to meeting the course requirement, a doctoral student must pass the Qualifying Examination, complete the dissertation under the supervision of the student's advisor and dissertation committee and pass the oral dissertation examination. In addition, a written dissertation proposal must be accepted by the dissertation committee at least six months prior to the oral dissertation examination. A doctoral candidate is expected to have at least one research paper published or accepted for publication in a fully refereed conference or journal prior to graduation. The following rules apply to the courses taken beyond the master's degree:

  1. Of the 18-credit minimum of coursework, a minimum of 12 credits must be in Computer Science and Engineering courses (excluding directed independent study credits) and a minimum of 9 credits of 6000-level courses must be completed.
  2. A maximum of 3 credits of directed independent study may be used to satisfy the minimum of 18 credits. In that case, the subject matter may not overlap the student's dissertation.
  3. Students must register for a minimum of 24 credits of dissertation.
  4. Students must have a GPA of 3.0 (out of 4.0 maximum) or better.
  5. All courses in the degree programs must be completed with a grade of "C" or better.
  6. Students must complete two semesters of CGS 5937 Graduate Seminar.

In addition, the following requirements must be met:

  1. Graduate coursework counted for the Ph.D. program must contain at least four graduate courses from the Data Science and Analytics course list below. Graduate courses completed during the master's degree program may also be used to meet this requirement.
  2. The student's Ph.D. dissertation research and scholarship must have a strong emphasis on one or more areas of data science and analytics, including but not limited to applied and/or theoretical areas.

BS to PhD

A minimum of 72 graduate credits is required beyond a bachelor's degree. A minimum of 42 credits of graduate coursework is required. All courses must be approved by the student's advisor. In addition to meeting the course requirement, a doctoral student must pass the Qualifying Examination, complete the dissertation under the supervision of the student's advisor and dissertation committee and pass the oral dissertation examination. The Qualifying Examination will normally be taken after the student has completed 24 credits of graduate coursework. In addition, a written dissertation proposal must be accepted by the dissertation committee at least six months prior to the oral dissertation examination. A doctoral candidate is expected to have at least one research paper published or accepted for publication in a fully refereed conference or journal prior to graduation. The following rules apply to the courses:

  1. Of the 42-credit minimum of coursework, a minimum of 27 credits must be in Computer Science and Engineering courses (excluding directed independent study credits) and a minimum of 18 credits of 6000-level courses must be completed.
  2. A maximum of 6 credits of directed independent study may be used to satisfy the minimum of 42 credits. In that case, the subject matter may not overlap the student's dissertation.
  3. Students must register for a minimum of 30 credits of dissertation.
  4. Students must have a GPA of 3.0 (out of 4.0 maximum) or better.
  5. All courses in the degree programs must be completed with a grade of "C" or better.
  6. Students must complete two semesters of CGS 5937 Graduate Seminar.

In addition, the following requirements must be met:

  1. Graduate coursework counted for the Ph.D. program must contain at least four graduate courses from the Data Science and Analytics course list below.
  2. The student's Ph.D. dissertation research and scholarship must have a strong emphasis on one or more areas of data science and analytics, including but not limited to applied and/or theoretical areas.

Data Science and Analytics

Title

Course No.

Hours
Introduction to Neural Networks CAP 5615 3
Introduction to Data Science CAP 5768 3
Social Networks and Big Data Analytics CAP 6315 3
Data Mining for Bioinformatic CAP 6546 3
Sparse Learning CAP 6617 3
Machine Learning for Computer Vision CAP 6618 3
Deep Learning CAP 6619 3
Artificial Intelligence CAP 6635 3
Natural Language Processing CAP 6640 3
Data Mining and Machine Learning CAP 6673 3
Information Retrieval CAP 6776 3
Web Mining CAP 6777 3
Advanced Data Mining and Machine Learning CAP 6778 3
Big Data Analytics with Hadoop CAP 6780 3
Computer Performance Modeling CEN 6405 3