S&T’s unique program will prepare graduate students through cross-disciplinary courses and flexibility with advanced elective courses in various disciplines. Graduates will be proficient in applying analytical tools and possess a deep understanding of their theoretical foundations.

This teaching approach will enable graduate students to evaluate limitations of existing methods and develop innovative solutions to complex problems. This educational approach addresses the increasing demand for professionals who can integrate knowledge across disciplines and adapt to the fast-evolving landscape of artificial intelligence and machine learning.

Degree options are designed to achieve balance between depth of knowledge acquired through specialization and breadth of knowledge gained through exploration.

The program’s emphasis on project-based learning ensures graduate students gain hands-on experience that prepares them for roles across a variety of sectors, including technology, healthcare, finance and manufacturing.

Mathematics and Statistics Track

This track emphasizes probability modeling, statistical theory, and mathematical foundations that support advanced data analysis and machine learning. Students gain the depth needed to understand not just how to apply data science methods, but why they work.

Computer Science Track

This track focuses on computational methods, artificial intelligence and scalable data systems. Students develop strong programming and algorithmic skills for building data-driven solutions in complex computing environments.

Data scientists generally use various computational methods to make sense of large sets of data by combining computer science and mathematics to gain insights and analyze trends. It is a growing field that works to better understand the world through data mining, deep learning and reasoning, and artificial intelligence.

Data scientists are needed in fields such as health care, banking and finance, research and development, information technology, and more.

The analysis of Big Data is an emerging phenomenon and computing systems today are generating 15 petabytes of new information every day – approximately 80% of data generated daily is textual and unstructured data.

The field of data analytics identifies trends, creates predictive models for forecasting, and optimizes business processes for enhanced performance. Three main categories of analytics are:

• Descriptive - the use of data to find out what happened in the past.
• Predictive - the use of data to find out what could happen in the future.
• Prescriptive - the use of data to prescribe the best course of action for the future.