M.S. in Data Science & Strategic Analytics
The Data Science and Strategic Analytics (DSSA) Program at Stockton is a self-standing, master’s degree program. A student entering the program will acquire substantial experience in sophisticated, industry standard, computational software and programming tools that will allow the student to explore data driven problems in the science, business, social science, medicine and/or the humanities.
Students will also develop skills in data analysis, presentation, and visualization; skills that will permit them to visualize results and make predictions. The course work is supplemented with real world projects and/or internships with industry providing experience and networking opportunities in industry or research.
In 2013 IBM estimated that two and a half million terabytes of data were being created every day. This is the equivalent of over 300 million HD movies! Ninety percent of the world’s data was generated in just the past two years. Data is created by: individuals (through social networks and smartphones); machines (through real-time, network connected, sensors – “the internet of things”); business and commerce (e.g. transaction records); science (e.g. bioinformatics, large scale simulation). Much of this data is real time and georeferenced through GPS. Making sense of this vast sea of data for the use and benefit of society is considered an imperative of the coming years, indeed many companies are already strategizing for “big data”. Data scientists develop solutions for gathering, cleaning, archiving, analyzing and visualizing data for the purposes of making informed decisions.
Some examples of data science projects include:
- Business: Use historical discounting data from a department chain store at one thousand locations to predict how sales vary with department, season and location.
- Entertainment: Perform a sentiment analysis on the tweets about summer blockbuster movies sentiments and use to predict future box office takings based on movie genre, actors etc.
- Science: Analyze the jpg images of one million galaxies to categorize them according to their morphology.
- Health: Predict disease likelihood by exploring and correlating patient case history and genetic databases.
- Criminal Justice: Gather and visualize real time crime statistics for a city for efficient resource deployment.
- Education: Create a web based dashboard for describing student performance metrics across a school district.
The Master’s degree program consists of 30 credit hours (10 graduate courses) that can be completed in full-time (or part-time study). In full-time study it may be completed in one calendar year (Fall, Spring, Summer). The courses are offered online as a hybrid (students will meet with faculty once a week at Stockton's Kramer Hall Instructional Site).
The self-standing Master’s degree program consists of 30 credit hours (10 graduate courses) that can be completed in full-time or part-time study. The courses are offered online as hybrid or blended courses. Full-time study is the preferred route and in this mode the degree may be completed in one calendar year.
DSSA Curriculum - 30 credits
All courses are for 3 graduate credits.
DSSA 5001 Introduction to data science and analytics
DSSA 5101 Data exploration
DSSA 5102 Data gathering and warehousing
DSSA 5103 Data Visualization*
DSSA 5104 Data Analysis and Operations Research
DSSA 5201 Machine Learning
DSSA 5202 Case Studies in Analytics
DSSA 5203 Data Stewardship
DSSA 5301 Communicating Data Stories
DSSA 5302 Data Practicum
For course descriptions, please visit The University's Course Catalog.
Fall enrollment only: July 1
- Baccalaureate degree from a regionally accredited institution of higher education.
- Minimum undergraduate GPA of 3.0 and an average GPA of 3.2 or better derived from all quantitative courses.
Students with undergraduate degrees in quantitative subject areas (e.g. science, math, computer science, business) with experience in descriptive statistics, college algebra, data processing/analysis, computer and mathematical skills will make up the vast majority of applications and enrollments. A typical applicant would be expected to demonstrate advanced undergraduate coursework in statistics and computing. All applicants will be evaluated individually by a faculty committee.
To be considered for admission to the DSSA master's program, applicants must submit the following:
- Discover Stockton Online Application
- Application fee: $50 (non-refundable), submitted with your online application
- Graduate application essay describing computing experience
- Three current letters of recommendation sent electronically via the Discover Stockton Application (preferably at least one from a faculty member).
- Official transcripts from all colleges/universities attended (including Stockton) showing successful completion of a baccalaureate degree from a regionally-accredited institution.
- The TOEFL Exam is required of students for whom English is the second language.
Acceptance into the DSSA program will be based on a review of the entire application packet. Admission to the program is competitive and acceptance is not guaranteed. Specific minimum requirements may be waived at the discretion of the DSSA Admissions Committee. Additionally, students lacking in the required prerequisites may be asked to take remedial online courses in computing and/or statistics.
Direct Entry is available for Stockton students who meet the requirements.
Please visit the Direct Entry page for more information.
Get up to speed with the latest data science technologies including Linux, Python, and R Basics by taking free online courses offered through www.EdX.org. These courses are especially helpful to those considering applying and in need of some remediation prior to starting graduate classes.
Develop a good working knowledge of Linux using both the graphical interface and command line, covering the major Linux distribution families.
Dig deeper into data structure basics.
Learn the basic building blocks of R through this series that covers data wrangling with dplyr, visualization with ggplot2, probability, inference, regressions and machine learning.
Standardized test scores (GRE or MAT) are not required for admission. However, proof of English proficiency is required of students for whom English is the second language.
Yes. Students may take up to two classes (6 credits) as a non-matriculated student. Please fill out the Online Graduate Non-Matriculated Registration form.
Provided that the courses sufficiently match corresponding Stockton courses, the University will accept up to nine credits of appropriate, relevant graduate credit from other regionally-accredited colleges and universities. Graduate credit will only be accepted upon application to Stockton. Once students have matriculated at the University, students will be required to finish the remainder of their course work at Stockton.