COURSE CURRICULUM

The Master of Science in Data Science at San José State University is a 36-unit graduate program jointly offered by the Departments of Computer Science and Mathematics and Statistics. It is designed to provide advanced training in both computational and statistical methods for analyzing and interpreting large-scale data. The program integrates core concepts from computer science, mathematics, statistics, and machine learning to prepare students for data-driven careers in industry, government, and research.The curriculum consists of 27 units of core coursework, covering key areas such as artificial intelligence, database management systems, statistical modeling, regression analysis, data visualization, clustering methods, and web intelligence. Students also take a required graduate-level technical writing course to strengthen their ability to communicate technical findings effectively. In addition, students choose one advanced course in either machine learning classification or machine learning theory to deepen their specialization. The program ensures balanced training by requiring students to complete coursework from both computer science and mathematics departments.Students must also complete a 3-unit elective course selected with advisor approval, allowing further specialization based on individual interests such as advanced machine learning, data systems, or applied statistics.The culminating experience requires 6 units of advanced project or thesis work conducted over two semesters. Students must form a faculty advisory committee, including a primary advisor and additional faculty members, and obtain approval for their research topic. The final requirement includes producing a formal research manuscript and successfully defending it through a comprehensive oral examination. This ensures students demonstrate both technical expertise and research capability in data science.Overall, the program prepares graduates for careers as data scientists, machine learning engineers, statistical analysts, and research professionals. It emphasizes strong foundations in computation, statistics, and machine learning, along with practical research experience and communication skills needed to solve complex real-world data problems.