Data Science
Vijay Voddi, M.S., Director, Master of Science in Data Science Program
Master of Science in Data Science
The Master of Science in Data Science, a 36 credit degree program, is intended for students who have completed undergraduate degrees in science, mathematics, computer science or engineering and are interested in pursuing careers in industry-specific analytical fields (e.g. technology, pharmaceutical, research, government, public health, entrepreneurship, finance, business, etc.).
The Data Science degree program uses real-world problems and situations to prepare graduates for roles as strategic thought leaders who leverage predictive modeling to drive decision making. Students will develop in depth understanding of the key technologies in data science and business analytics: data mining, machine learning, visualization techniques, predictive modeling, and statistics. Students will practice problem analysis and decision-making. Students will gain practical, hands-on experience with statistics programming languages and big data tools through coursework and applied research experiences.
Program Availability
The Data Science program will be offered on a semester schedule and is designed for both full-time and part-time study.
Degree Requirements
The degree requires 36 semester hour credits. A capstone course is required and will be taken the final semester of coursework.
Graduate Internship
As of January 1, 2016, completion of an internship related to Data Science is required for all students except: those who have 3+ years of professional work experience; those with full-time employment during the length of the program; and those who are participating in the exchange program. The graduate internship can start in the fourth trimester of classes. Please consult your program advisor to determine if it is possible to obtain a waiver.
Advisement
Saint Peter's University assigns an academic advisor to every candidate.
Time Limitation
Students are expected to enroll continuously until their programs are completed. Students are required to maintain satisfactory academic progress by maintaining the required grade point average and accumulating sufficient credits within the stipulated time frame of five years. By federal regulation, F-1 International students must enroll as full-time students, so their time to completion will be considerably shorter.
Curriculum - Master of Science in Data Science - Traditional track
The Master's in Data Science program is divided into two levels as detailed below.
| Required Core Courses | 27 | |
| Introduction to Data Science | ||
| Data Analysis and Decision Modeling | ||
| Data Management Systems | ||
| Python in Data Science | ||
| Data Mining | ||
| Data Visualization | ||
| Machine Learning | ||
| Data Ethics and Artificial Intelligence | ||
| Capstone: Big Data & Data Science | ||
| Electives - Take 3 courses from the following: | 9 | |
| Big Data Analytics | ||
| Predictive Analytic & Financial Modeling | ||
| Business Analytics | ||
| Marketing Analytics & Operation Research | ||
| Data Science and Health | ||
| Industry Experience- Complete after 4th trimester | ||
| DS-597 | Applied Research Experience | 0 |
| or DS-598 | Applied Industry Experience | |
| Total Credits | 36 | |
Master of Science in Data Science Program - Professional Hybrid track
In addition to the traditional curriculum, students must complete an internship (DS-598 or DS-599) every trimester.