Data Science Ph.D. Plan of Study
Data Science Core (24 cr.)
- INFO I501 Introduction to Informatics (3 cr.)
- LIS S511 Database Design (3 cr.) or CSCI 54100 Database Systems (3 cr.)
- STAT 51100 Statistical Methods I or higher (3 cr. requires approval)
- INFO H515 Data Analytics (3 cr.) or CSCI 57300 Data Mining (3 cr.)
- INFO H516 Applied Cloud Computing for Data Intensive Sciences (3 cr.) or CSCI 59000 Cloud Computing (3 cr.)
- INFO H517 Visualization Design, Analysis, and Evaluation (3 cr.) or CSCI 55200 Data Visualization (3 cr.)
- LIS S541 Information Policy (3 cr.)
- INFO I575 Informatics Research Design (3 cr.)
Methods Courses (18 cr.)
- CSCI 52000 Computational Methods in Analysis (prerequisites: CSCI 23000 Computing II or equivalent and MATH 35100 Elementary Linear Algebra OR MATH 511 Linear Algebra and Applications)
- CSCI 58000 Algorithm Design, Analysis, and Implementation
- NURS-L 650 Data Analysis for Clinical and Administrative Decision-Making (3 cr.)
- NURS-R 612 Interpretive Data Analysis (2 cr.)
- PBHL-B 515 Biostatistics Practicum (3 cr.)
- PBHL-B 527 Introduction to Clinical Trials (3 cr.)
- PBHL-B 546 Applied Longitudinal Data Analysis (3 cr.)
- PBHL-B 571 Biostatistics Method I: Linear Models in Public Health (4 cr.)
- PBHL-B 621 Advanced Statistical Computing (3 cr.)
- PBHL-B 636 Advanced Survival Analysis (3 cr.)
- PBHL-B 646 Advanced Generalized Linear Models (3 cr.)
- PSY 60000 Statistical Inference (3 cr.)
- PSY 60100 Experimental Design (3 cr.)
- PSY 60800 Measurement Theory and Interpret Data (3 cr.)
- PSY 64000 Survey of Social Psychology I (3 cr.)
- PSY-I 643 Field Methods & Experimentation (3 cr.)
- SOC-R 551 Quantitative Methods (3 cr.)
- SOC-R 559 Intermediate Soc. Statistics (3 cr.)
- STAT 51100 Statistical Methods 1 (3 cr.)
- STAT 51200 Applied Regression Analysis (3 cr.)
- STAT 51600 Basic Probability Applications (3 cr.)
- STAT 51900 Introduction to Probability (3 cr.)
- STAT 52100 Statistical Computing (3 cr.)
- STAT 52200 Sampling and Survey Techniques (3 cr.)
- STAT 52400 Applied Multivariate Analysis (3 cr.)
- STAT 52500 Generalized Linear Model (3 cr.)
- STAT 52800 Mathematical Statistics I (3 cr.)
- STAT 52900 Applied Decision Theory and Bayesian Statistics (3 cr.)
- STAT 53600 Introduction to Survival Analysis (3 cr.)
- STAT 61900 Probability Theory (3 cr.)
- STAT 62800 Advanced Statistical Inference (3 cr.)
May include up to 6 credit hours of INFO-I 790 Informatics Research Rotation.
Specialization (18 cr.)
- Disciplinary Affinities (0–6 cr.)
- Minor (12–18 cr.)
The student must complete a minor within a domain appropriate to the chosen specialization and/or research area. All courses must be graduate-level and taken outside the Data Science program.
Qualifying Examination, Written and Oral
A student must successfully complete a written and oral qualifying examination before the fifth semester of the program. The written exam has a breadth part and a depth part. The breadth part covers the program’s core courses. The depth part additionally covers material from the student’s research.
The oral exam takes place shortly after the student passes the written exam. The oral exam is based on the student’s response to the written exam and the core courses. The both the written and oral exams are prepared and evaluated by faculty in the school who are familiar with the content of the core courses.
The student must pass both the written exam and the oral exam before advancing to candidacy. The student may retake once either the written exam or oral exam, but not both, if they do not pass that part on the first attempt. For further details, consult with the data science program director.
Dissertation (30 cr.)
A dissertation is a written elaboration of original research that makes creative contributions to the student’s chosen area of specialization. The student will enroll multiple times in INFO I890 Thesis Readings and Research (1-12 cr.) while completing the dissertation. All requirements must be completed within seven years of passing the qualifying exams. The dissertation process includes the following components:
- Proposal: This is an in-depth oral review undertaken by students who have made significant progress in their research. The proposal will be defended at a public colloquium. The student must complete the proposal within one year of passing the qualifying exams.
- Defense: The student must defend his or her dissertation in an open seminar scheduled when doctoral research is almost complete.
Please refer to the IUPUI Graduate School Bulletin for more details on the dissertation process.