Data Science Doctoral Degree

Program Overview

Harrisburg University's Data Sciences Ph.D. program equips students with advanced knowledge and skills in data science methodologies. The program consists of coursework, research, and fieldwork, culminating in original research and a final examination. Graduates are prepared for influential roles in analytical teams across disciplines, contributing to the advancement of data science practices.

Program Outline

Degree Overview:

The Data Sciences Ph.D. program at Harrisburg University aims to create scientifically minded and technically proficient professionals with a comprehensive understanding of data science methodologies and the intellectual depth to contribute influential perspectives to analytical teams across disciplines.

Outline:

The program consists of two phases: a learning phase and a research phase. The learning phase includes coursework, seminars, research, and fieldwork that contribute to the student's knowledge in the program of study. The research phase focuses on the student's original research, culminating in their final examination. The following courses comprise the 36 semester hours required for the Ph.D. in Data Sciences:

• ANLY 705 – Modeling for Data Science (3 credits)
• ANLY 710 – Applied Experimental & Quasi-Experimental Design (3 credits)
• ANLY 715 – Applied Multivariate Data Analysis (3 credits)
• ANLY 720 – Data Science from an Ethical Perspective (3 credits)
• ANLY 725 – Research Seminar in Unstructured Data (3 credits)
• ANLY 730 – Research Seminar in Forecasting (3 credits)
• ANLY 735 – Research Seminar in Machine Learning (3 credits)
• ANLY 740 – Graph Theory (3 credits)
• ANLY 745 – Functional Programming Methods for Data Science (3 credits)
• ANLY 755 – Advanced Topics in Big Data (3 credits)
• ANLY 760 – Doctoral Research Seminar (3 credits)
• ANLY 761 – Research Seminar in Unstructured Data (3 credits)
• ANLY 762 – Research Seminar in Forecasting (3 credits)
• ANLY 763 – Research Seminar in Machine Learning (3 credits)