Image: The Department of Statistics is pleased to report the successful completion of the first semester of the new fully online Master of Science in Applied Data Science (MS-ADS). Designed for working professionals, the 30-credit program provides a flexible, two-year pathway for students who seek advanced technical training while balancing full-time work and personal commitments. The interdisciplinary curriculum builds hands-on expertise in Python, R, SQL, statistical modeling, data visualization, machine learning, natural language processing, and deep learning. With a focus on real-world application and modern computational tools, the program prepares graduates to contribute to data-driven decision making across a wide range of industries. This fall, the program welcomed its inaugural cohort of 16 students. Fourteen students reside in Georgia and two are joining from out of state, reflecting strong statewide interest in applied data science education. Students in the first cohort represent a variety of professional backgrounds and report strong progress in foundational programming and analytics as they complete their first term. "Our first cohort has shown remarkable dedication in balancing graduate study with work and family responsibilities," said Man Basnet, Associate Director of the MS-ADS program. "We are proud of the momentum they have built this semester and look forward to supporting their continued growth as they move into more advanced topics." The department is also finalizing a 10-member Industry Advisory Board composed of professionals in analytics, artificial intelligence, and data science leadership roles. The board will support ongoing curriculum alignment with workforce needs, strengthen relationships with employers, and help guide long-term program development. Key curriculum topics include: • Programming for data science in Python and R• Database design, SQL, and data engineering foundations• Machine learning, clustering, and classification• Natural language processing and deep learning• Distributed and cloud-scale data processing• Applied statistical inference and analytics Type of News/Audience: Departmental
