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Data Analytics Foundations for Accountancy II

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Data Analytics Foundations for Accountancy II builds upon concepts introduced in the first course to enable students to obtain, explore, and analyze richer and more complex data sets. Students will first learn how explore and analyze multi-dimensional data sets, before learning how to obtain text data embedded within websites and how to analyze text data by using standard Python techniques and regular expressions. Module #1: Applied Data Analytics Module #2: Introduction to Text Analytics Module #3: Introduction to Data Persistence Module #4: Introduction to Python and Databases Module #5: Introduction to Probability Module #6: Introduction to Time Series Data Module #7: Introduction to Time Series Analysis Module #8: Introduction to Density Estimation


Robert Brunner

Associate Dean for Innovation and Chief Disruption Officer and Professor of Accountancy and Arthur Andersen Faculty Fellow

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