Bachelor of Applied Statistics and Data Science

Introduction
The Bachelor of Applied Statistics and Data Science (ASDS) is a four-year, full-time undergraduate program offered by the Department of Mathematics and Sciences at Prince Sultan University (PSU). It is designed to meet the growing demand for professionals who can turn complex data into actionable insights. As data continues to transform the way industries operate, this program equips students with the analytical and technical skills needed to lead in today’s data-driven world.
This interdisciplinary program empowers students with advanced competencies in statistical analysis, machine learning, data visualization, and predictive modeling, combining mathematical theory with hands-on problem-solving. Students learn to extract actionable knowledge from complex datasets, enabling businesses to improve performance, manage risk, and forecast outcomes with confidence
Applied Statistics provides the backbone of data-driven decision-making. It encompasses a wide range of techniques used to interpret data, uncover patterns, and support forecasting across real-life domains—from healthcare and engineering to finance and the social sciences. As a modern mathematical discipline, it plays a vital role in identifying what information is reliable and which predictions can be trusted
Data Science, on the other hand, brings together computational tools, algorithmic thinking, and scientific methods to analyze massive datasets and draw impactful conclusions. In an era where data is a strategic asset, data scientists are instrumental in solving complex business challenges such as fraud detection, customer lifetime prediction, and employee retention analysis.
The ASDS program at PSU also emphasizes research proficiency, ethical responsibility, and effective communication, ensuring graduates are well-prepared to lead innovation in diverse fields. Whether guiding policy decisions, enhancing healthcare delivery, or optimizing corporate strategy, ASDS graduates are equipped to make a measurable difference in a data-centric world.