M.S. in Data Science and Analytics

Program Overview

The M.S. in Data Science and Analytics (MS DSA) is a 33-credit graduate program that can typically be completed in 1.5 to 2 years. It offers flexibility with options for full-time, part-time, and a 100% online delivery mode, allowing students to balance their studies with work and personal commitments. The program aims to prepare students to be productive contributors in various professions dealing with complex data, focusing on the entire data lifecycle from collection to communication of results. It draws upon the outstanding academic talent across multiple departments at SUNY Poly, including computer science, mathematics, social and behavioral sciences, and health sciences.

STEM-Designated: Yes, the M.S. in Data Science and Analytics program at SUNY Polytechnic Institute is STEM-designated. This is a crucial benefit for international students, as it makes them eligible for the STEM Optional Practical Training (OPT) extension, providing up to an additional 24 months of work authorization in the U.S. after completing their degree.

Curriculum: The MS DSA curriculum is interdisciplinary and comprehensive, comprising six required core courses (18 credits), a capstone experience (3 credits), and four elective courses (12 credits). Core courses cover fundamental knowledge and skills in statistical inference, data collection and design, data analytics tools, visual analytics and communication, introduction to machine learning, and big data platforms and analytics. For the capstone, students can choose between an internship, a practical project, or a more research-oriented thesis. Elective courses offer significant flexibility, allowing students to specialize within areas like computer science, mathematics, social sciences (e.g., criminology), or health informatics, or to combine courses across different specializations with advisor approval. The curriculum emphasizes highly marketable techniques using various data analytics tools, computer coding (e.g., Python), machine learning, geospatial programming, and data visualization.

Research Focus: The M.S. in Data Science and Analytics program at SUNY Poly fosters an applied research focus. While a thesis option is available for the capstone experience, the program emphasizes extracting knowledge from data through the design of analytics models and the ethical collection and preparation of multi-modal data. Students have the opportunity to interact and work with faculty who have diverse research and teaching interests across various disciplines. The program's core components in statistical inference, machine learning, and big data platforms directly prepare students to engage with and contribute to data-driven research. Faculty are involved in exploring responsible AI frameworks and leveraging AI for sustainable development, including developing AI-driven solutions for real-world problems.

Industry Engagement: SUNY Polytechnic Institute is dedicated to making its Data Science and Analytics graduates "exceptionally employable." The program offers an internship option for its capstone experience, providing students with applied-skills training with industry partners in industrial organizations. The curriculum itself is designed to provide advanced practical training in in-demand modern skills that are essential for informed, evidence-based decision-making across industries. The university emphasizes professional skills development in project management, communications, and data governance for effective collaboration. Faculty members often have professional experience in their respective fields, ensuring the curriculum remains relevant to industry needs. The program's strong ties to diverse departments and its focus on applied skills ensure graduates are prepared for a variety of roles across sectors.

Global Perspective: The M.S. in Data Science and Analytics program at SUNY Polytechnic Institute inherently incorporates a global perspective by addressing the universal challenges and opportunities presented by complex data. Data science principles and applications are globally relevant, transcending national borders and diverse industries. The program attracts a diverse international student body, enriching the learning environment with varied cultural viewpoints and preparing graduates to collaborate in an increasingly interconnected global workforce. By equipping students with the skills to work with multi-modal data and to extract knowledge ethically, the program prepares them to contribute to global problem-solving, whether in international business, public health initiatives, or scientific research collaborations.