COURSE CURRICULUM

The Master of Science in Data Analytics program offers a comprehensive 30-semester-hour curriculum designed to develop expertise in data science, analytics, and business intelligence. Students begin with an introductory course, DASC 5100 Programming Fundamentals, which provides foundational skills in programming; this course may be waived if the student has completed equivalent undergraduate coursework. The core courses, totaling 21 semester hours, cover essential topics including ethics for data analytics (DASC 5150), mathematics for data science (DASC 5200), advanced programming (DASC 5300), data analysis and visualization (DASC 5320), machine learning (DASC 5383), and data simulation, Bayesian modeling, and inference (DASC 5400). These courses build both the theoretical knowledge and practical skills necessary to analyze complex datasets, implement predictive and prescriptive models, and communicate insights effectively. The curriculum culminates in a capstone project (DASC 6398), where students apply their learning to a real-world analytics problem, demonstrating proficiency in data-driven decision-making. Additionally, students complete 9 semester hours of electives, allowing customization of their learning based on career goals. Elective options include business analytics courses in predictive and prescriptive analytics, databases and data warehousing, operations management, and business intelligence. This combination of foundational, core, and elective courses ensures that graduates are prepared for diverse professional roles, including data analyst, data scientist, machine learning engineer, and business intelligence specialist, equipped with both technical skills and strategic insight.