Master of Science in Data Science
Saint Peter's University
Jersey City, USA
Blended, Distance Learning, On-Campus
Full time, Part time
USD 795 / per credit *
01 Jun 2023
Earliest start date
* Academic Year 2022-2023 tuition: Online: $795 per credit; Hybrid: $945 per credit
Help forge the future of Big Data.
With the exponential growth of big data over the past few years, the need for data scientists becomes more and more pronounced and urgent.
The Data Science Institute at Saint Peter’s University is training the next generation of Data Science students by offering a cutting-edge academic program to meet such demands and train the next generation of data scientists. The Institute works closely with industry thought leaders to bring innovative ideas to market.
The Data Science program integrates scientific methods from statistics, computer science, and data-based business management to extract knowledge from data and drive decision-making. Our curriculum provides students with a rigorous course of study in big data technologies, applications, and practices a pathway for student internships and full-time employment. Graduates are prepared to meet the challenges at the intersection between big data, business analytics, and other emerging fields.
In addition to the Masters's program, we offer customized certificate and training courses in the field of analytics. One-semester preparatory courses are designed for graduate students and tailored for international studies to gain professional industry.
At A Glance
- Degree Awarded: Master of Science in Data Science
- Course Locations: Jersey City Campus
- Program Duration: 36 Credits: A full‐time student taking 24 credits/year should complete in 1.5 years.
- Calendar: Trimester
- Course Format: Classes meet in person Monday to Friday during the day or during the evening.
Accelerated BS to MS in Data Science Program
You can earn your undergraduate degree and an MS in Data Science in five years through our Accelerated Program.
Data Science is the discipline that integrates scientific methods from statistics, computer science, and business management to extract knowledge from data to drive decision-making. This program is designed for students with a background in computer science, applied science, business, or economics. For preparedness, students need to be currently enrolled in a BS program.
The Institute brings industry leaders, academics, and researchers together to create a unique program tailored to the career needs of professionals and students. Industry partners, including IBM, American Express, Red Hat, Oracle, Pfizer, UPS, and Verisk Analytics, serve on the advisory board to address the need for advanced analytics talent in industry.
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 a 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.
The Data Science program will be offered on a semester schedule and is designed for both full-time and part-time study.
The degree requires 36-semester hour credits. A capstone course is required and will be taken during the final semester of coursework.
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 first semester of classes. Please consult your program advisor to determine if it is possible to obtain a waiver.
Saint Peter’s University assigns an academic advisor to every candidate.
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.
- Introduction to Data Science
- Data Analysis and Decision Modeling
- Database and Data Warehousing
- Statistical Programming
- Data Mining
- Big Data Analytics
- Data Visualization
- Machine Learning
- Predictive Analytics and Experimental Design
- Data Law, Ethics, and Privacy
- Business Analytics
- Capstone: Business Analytics
Total Credits: 36
Data Science Graduate Internship
Completion of a graduate 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 an exchange program. The graduate internship can start in the first semester of classes. Please consult your program adviser to determine if it is possible to obtain a waiver.
- Develop a depth understanding of the key technologies in data science and business analytics: data mining, machine learning, visualization techniques, predictive modeling, and statistics.
- Practice problem analysis and decision-making.
- Gain practical, hands-on experience with statistics programming languages and big data tools through coursework and applied research experiences.
Students who have completed the MS in Data Science and Business Analytics Program will be able to:
- Apply quantitative modeling and data analysis techniques to the solution of real-world business problems, communicate findings, and effectively present results using data visualization techniques.
- Recognize and analyze ethical issues in business related to intellectual property, data security, integrity, and privacy.
- Apply ethical practices in everyday business activities and make well-reasoned ethical business and data management decisions.
- Demonstrate knowledge of statistical data analysis techniques utilized in business decision-making.
- Apply principles of Data Science to the analysis of business problems.
- Use data mining software to solve real-world problems.
- Employ cutting-edge tools and technologies to analyze Big Data.
- Apply algorithms to build machine intelligence.
- Demonstrate the use of teamwork, leadership skills, decision-making, and organization theory.
By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills and the know-how to use Big Data to make effective decisions.
- Computer Forensics
- Data Scientist
- Operations Data Analyst
- Computer Forensics
- Data Scientist
- Operations Data Analyst
English Language Requirements
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