{'fraction_non_alphanumeric': 0.02103960396039604, 'fraction_numerical': 0.0, 'mean_word_length': 5.420634920634921, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Data Science for All: A Tale of Two Cities

In this poster the authors report on experiences in teaching an introductory course in Data Science at two different institutions. Their approaches were informed by the aims of their NSF-funded project: to provide insight on learning goals, central data science topics, content modules, and a framework for implementing a flipped classroom approach to introduce data science to students with various technical backgrounds. The authors, investigators on the grant mentioned above, are a collaborative team of computer scientists and a statistician working to create flipped material for an introductory data science class. After ITiCSE the materials described in the poster will continue to be available in Ensemble, at http://computingportal.org/datascienceflipped