COURSE CURRICULUM

The Master of Science in Applied Data Intelligence is a 30-unit graduate program designed to build strong technical and analytical expertise in modern data science and artificial intelligence applications. The program begins with 15 units of core courses that provide a foundation in mathematical methods, big data technologies, data visualization, machine learning, and deep learning. These courses include DATA 220, DATA 228, DATA 230, DATA 245 (which also satisfies the GWAR requirement), and DATA 255. Together, they equip students with essential skills to understand, process, and model complex data for real-world applications.In addition to the core curriculum, students complete 9 units of electives by selecting one specialization track. The Analytics Technologies track includes courses in database systems, data mining, and large language model applications, while the Data Engineering track focuses on data warehousing, distributed systems, and generative model applications. This structure allows students to develop deeper expertise in a focused area aligned with their career goals in data analytics, artificial intelligence, or data infrastructure.The program concludes with a 6-unit culminating experience, which can be completed as either a thesis or a project. Plan A involves DATA 299A and DATA 299B, where students conduct independent research for a formal thesis. Plan B involves DATA 298A and DATA 298B, which focus on applied project work solving practical data intelligence problems. In total, students must complete 30 units and maintain a minimum GPA of 3.0 in both the program and university requirements to graduate. This structure ensures graduates are well-prepared for advanced careers in data science, machine learning, analytics engineering, and related fields.