Offered Online and On Campus
Overview
The MS in Data Science and Analytics (MS DSA) is a flexible program with courses offered on-campus and online depending upon your specialization interests. The MS DSA prepares students for many professions dealing with complex data, in particular those that relate to the ethical collection, exploration and preparation of multi-modal data, the design of analytics models to extract knowledge from data, and the effective communication of data analysis results to decision-making constituencies. Information about the MS DSA program is available on the SUNY Poly MS DSA program page.
Career Paths
The ability to effectively analyze and interpret data is essential for professionals in almost every industry. The MS in Data Science and Analytics program is designed to provide students with the knowledge and skills needed to succeed in this rapidly growing field. Graduates will learn the latest tools and technologies to analyze large and complex data sets, preparing them for a diverse range of career paths, such as:
- Data Analysts
- Data Engineers and Machine Learning Engineers
- Database Administrators
- Applications Architects
- Statisticians, and professionals in Risk Management and Market Research.
Recent Bureau of Labor Statistics data suggests a much faster-than-average growth in job outlook and solid career earnings in this field. With such a high demand for data professionals and the potential for lucrative careers, studying data analytics can be a wise investment decision for your future.
Program Requirements
The M.S. in Data Science and Analytics consists of 33 credit hours distributed as follows:
DSA Core Courses: 18 credit hours
DSA Specialization Electives: 12 credit hours
Thesis/Project/Internship: 3 credit hours
The MS in DSA program has an interdisciplinary nature, consisting of six required core courses, a capstone experience (internship, project, or thesis), and four elective courses chosen across specialization offerings from several academic departments of SUNY Polytechnic Institute. Students may choose to select four courses that fall within one specialization, or pick and choose courses across different specializations. Elective courses will be selected with the assistance of an academic advisor.
Core Required Electives: 18 credits (offered online or on-campus)
DSA 501 Statistical Inference
DSA 503 Data Collection and Design
DSA 504 Data Analytics Tools
DSA 506 Visual Analytics and Communication
DSA 507 Introduction to Machine Learning
DSA 508 Big Data Platforms and Analytics
Elective Courses: 12 credits (choose 4)
Mathematics (offered online or on-campus)
STA 510 Regression and Analysis of Variance
MAT 550 Time Series Analysis
MAT 515 Mathematical Methods in Computational
Science & Engineering
MST 570 Design and Analysis of Experiments
MST 680 Reliability and Quality Assurance
Biology (offered on-campus)
BIO 505 Data Analytics Tools for Bioinformatics
Computer Science (on-campus courses)
CS 542 Machine Learning
CS 540 Artificial Intelligence
CS 541 Database Systems
CS 523 Parallel Computing
CS 524 Distributed Systems
CS 538 Special Topics in Algorithms
Design and Digital Humanities (offered online only)
IDT 548 Contemporary Trends in Data Visualization
IDT 554 Advanced Web Development and Design
IDT 503 User Experience Design
IDT 534 Information Design
COM 548 Special Topics in Visual Analytics & Communication
IDT 555 Ethical and Legal Issues of the Information Age
Social and Crime Analytics (on-campus only)
SOC 520 Criminology
SOC 521 Crime and Social Policy
SOC 531 Social Network Analysis
SOC 533 Crime Mapping and GIS
SOC 538 Special Topics in Crime Analytics
Health Informatics (offered online only)
HI 501 Health Care Informatics
HI 509 Legal Issues in Health Care Informatics
HI 520 Standardized Code Sets & Medical Terminologies
HI 600 Quality Improvement in Health Care
HI 630 Clinical Decision Support Systems
Business Analytics (offered online only)
ACC 540 Intro to Forensic Accounting/Fraud Detection
ACC 641 Accounting Info Systems and Data Analytics
BLW 570 Business Law, Ethics, Intellectual Property
FIN 532 Investment Strategy
TIM 500 Project Management
Required Capstone: 3 Credits (choose one) (offered online or on-campus)
DSA 597 Internship
DSA 598 Project
DSA 599 Thesis
Degree Requirements Overview & Program Notes
To be considered for admission, all applicants to the MS Data Science and Analytics program must possess a baccalaureate degree from an accredited university or college with an average of B or better (a GPA of 3.0 on a 4.0 point scale).
All applicants must also demonstrate an academic background with relevant undergraduate courses in statistics, matrix methods, basic calculus and introductory computer programming. Candidates not meeting these requirements may be considered on a case-by case basis, which may include an invitation to take a bridge course to support preparedness for the curriculum.
Application for Graduate Admission and all required forms are available at http://sunypoly.edu/admissions/graduate.html.