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This program (formerly known as Business Intelligence and Analytics MSc) focuses on advancing data collection and organization methods while uncovering valuable insights within routine data to enhance decision-making processes. The curriculum extends artificial intelligence (AI), machine learning (ML), and decision science principles into business intelligence, data science, and business analytics applications. Students will concentrate on solving real-world challenges related to evolving IT infrastructure and growing data volumes through practical applications and case studies, while gaining thorough knowledge of foundational models and methodologies. The course also provides insights into how technological advancements influence data science, business intelligence, and analytics practices, preparing students to adapt to these developments. Two core themes are integrated throughout the program. The first builds expertise in utilizing diverse technologies, architectures, tools, and methodologies for data science, encompassing data warehousing, mining, distributed data management, and relevant AI/ML approaches. The second theme strengthens understanding of analytical algorithms and quantitative methods, including AI, ML, and Operational Research (OR) for data analysis and decision modeling across various applications. The final project reinforces taught concepts while allowing for specialized research in a chosen field. Learning methods incorporate lectures, tutorials, seminars, hands-on sessions, coursework, presentations, group projects, and training with industry-standard tools like R, Python, Simul8, Palisade Decision Tools, Tableau, and Oracle.