Data Science Concentration

ABOUT THE PROGRAM

The University of North Texas Information Science PhD Program (IS PhD Program) responds to the varied and changing needs of the information age, therefore offering the Data Science Concentration. The concentration is being offered jointly with UNT Department of Information Technology and Decision Sciences and UNT Department of Computer Science and Engineering with the ultimate goal of providing interdisciplinary training, research and professional services in data science. Students will take courses that will prepare them for conducting research on critical issues in data science and related areas as they pertain to the information science perspective.

 

Course Requirements

Students enrolled in the data science concentration will take courses from four blocks of courses:

1. Information Science Core Area (12 graduate credit hours)

  • INFO 6000 - Seminar in Information Science
  • INFO 6660 - Readings in Information Science
  • INFO 6700 - Seminar in Communication and Use of Information
  • INFO 6945 - Doctoral Seminar in Information Issues

2. Research Courses (minimum of 24 graduate credit hours, including doctoral dissertation hours)

  • INFO 6940 Inquiry and Research Design
  • Quantitative Research Methods/ Statistics (6 graduate credit hours in consultation with advisor)
  • Qualitative Research Methods (3 graduate credit hours in consultation with advisor)
  • Doctoral Dissertation Hours (minimum of 12 hours of INFO 6950 to be completed after passing the qualifying exam)

3. Data Science Concentration Core (15 graduate credit hours)

  • CSCE 5300 - Introduction to Big Data and Data Science
  • DSCI 5350 - Big Data Analytics (or equivalent, e.g., CMHT 6500 - Big Data Implementation in Social Network Analysis)
  • DSCI 5360 - Data Visualization for Analytics (or INFO 5709 - Data Visualization and Communication)
  • INFO 5500 - Foundational Principles in Knowledge Management
  • INFO 5502 - Analytic Tools, Techniques and Methods

4. Data Science Concentration Electives (a minimum of 9 graduate credit hours; the following is a partial list. Other relevant courses may be used upon approval).

  • INFO 5707 - Data Modeling for Information Professionals (or equivalent, e.g., BCIS 5420 - Foundations of Database Management Systems)
  • INFO 5717 - Networked Data Modeling and Processing
  • INFO 5735 - Usability and User Experience Assessment
  • INFO 5737 - Information and Cyber-Security (or equivalent, e.g., CSCE 5550 - Introduction to Computer Security)
  • INFO 6880 - Seminar in Information Science and Technology (when topic is “Social Network Analysis for Information Professionals”)
  • INFO 6880 - Seminar in Information Science and Technology (when topic is “Health Research Methodology”)
  • LING 5410 - Computational Linguistics I
  • LING 6060 - Data Analysis in Human Language Technology (HLT) I
  • LING 6130 - Natural Language Processing (or equivalent, e.g., CSCE 5290 - Natural Language Processing)
  • DSCI 5220 - Survey Analytics
  • DSCI 5260 - Business Process Analytics
  • DSCI 5310 - Risk and Life-Data Analysis
  • DSCI 5340 - Predictive Analytics and Business Forecasting
  • LTEC 6514 - Seminar on Advanced Research Topics in Learning Technologies and Information Sciences (or equivalent, e.g., LING 5560 - Discourse Analysis)
  • LTEC 6514 - Seminar on Advanced Research Topics in Learning Technologies and Information Sciences (when topic is “Scaling Methods”) (or equivalent, e.g., LING 5560 - Discourse Analysis)
  • DSCI 5250 - Statistical Techniques in Simulation
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