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Computer Systems: Students pursuing this specialization will gain depth of knowledge in the development, deployment, and analysis of the complex computer and information systems necessary for tackling large-scale data science problems.
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The specialization course groupings are as follows. While selecting all 3 courses from the same category is advised for students seeking a focus, students may also choose courses across categories to suit their interests, if they prefer that approach. Students within the data science major will have the opportunity to pursue an area of specialization through the selection of elective courses in a targeted direction relating to data analytics, computer systems, modeling, or data science in context.
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CS 1501 - ALGORITHMS AND DATA STRUCTURES 2.CS 1675 - INTRODUCTION TO MACHINE LEARNING.STAT 1361 - STATISTICAL LEARNING AND DATA SCIENCE.The critical issue of the ethical use of data will also be addressed in the context of data science. Skills will be developed in the description and analysis of data in terms of sources of variability and key relationships, the development of algorithms and data handling skills to extract and interpret information from complex data sets, as well as in the visualization and communication of results. This is where students become data scientists, integrating skills from the foundational areas to develop expertise in the realm of data. Students wishing to pursue graduate studies or mathematical directions related to data science are advised to also take MATH 0240.Mathematically advanced students may replace STAT 1151.Mathematically oriented students should take MATH 1180.STAT 1152 - INTRODUCTION TO MATHEMATICAL STATISTICS / STAT 1632.STAT 1151 - INTRODUCTION TO PROBABILITY / STAT 1631 - INTERMEDIATE PROBABILITY.MATH 0480 - APPLIED DISCRETE MATHEMATICS / CS 0441 - DISCRETE STRUCTURES FOR CS.MATH 0280 - INTRO TO MATRICES & LINEAR ALG / MATH 1180 - LINEAR ALGEBRA 1.MATH 0230 - ANALYTIC GEOMETRY AND CALCULUS 2.MATH 0220 - ANALYTIC GEOMETRY AND CALCULUS 1.CS 0445 - ALGORITHMS AND DATA STRUCTURES 1.CS 0401 - INTERMEDIATE PROGRAMMING USING JAVA.These courses are drawn from three main disciplines (CS/IS, Math, and Statistics) and include an introductory course in the fundamental skills of working with data (Python/R programming, exploratory data analysis, data visualization): Courses in this area will help students develop baseline computational capabilities, will teach students to think about data in a statistical framework, and will introduce students to fundamental mathematical concepts arising in data analysis. The foundational courses provide students with fundamental knowledge across four "literacies": data, algorithmic, mathematical, and statistical.
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Completing this major will prepare students to work as a data science professional or to pursue graduate study in a direction involving data in a significant way.
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Students will develop expertise that connects theory to the solution of real-world problems, and be able to specialize their studies towards a more specific career focuses. This undergraduate major allows students to gain critical skill sets that span key areas of statistics, computing, and mathematics, with foundational training providing literacy in four areas (data, algorithmic, mathematical, and statistical) that every student needs to master data science. Our major in Data Science (offered jointly with the Dietrich School of Arts & Sciences Departments of Mathematics and Statistics) will enable students to participate in this data revolution. Such skills are interdisciplinary, involving ideas typically associated with computing, information processing, mathematics, and statistics as well as the development of new methodologies spanning these fields. These changes have sparked great demand for individuals with skills in managing and analyzing complex data sets. The rapidly expanding collection of massive amounts of data is leading to transformations across broad segments of industry, science, and society.