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Emphasizes developing graduates' numerical and analytical skills.
Students will acquire statistical proficiency for examining and presenting both basic and intricate data collections from diverse origins, including disease indicators, genomic information, and corporate datasets. This prepares graduates to excel in the competitive data science field across computing, business, and scientific disciplines.
Educational Objectives
Utilize comprehensive data science understanding across various big data scenarios, both theoretical and applied.
Employ critical thinking to assess, understand, and frame complex data science challenges.
Apply innovative thinking to foresee obstacles and develop big data solutions.
Leverage digital tools, information skills, and numerical ability to gather, assess, and integrate pertinent data from numerous sources.
Demonstrate effective communication within statistical discussions spanning diverse data science subjects.
Conduct and share data science evaluations with cultural awareness and ethical consideration, including indigenous perspectives.
Collaborate effectively while showing leadership in applying societal, environmental, and moral principles.
Display independent learning and professional responsibility through self-directed development and sound decision-making.