J. Cumby, M. Degiacomi, V. Erastova, J. Güven, C. Hobday, Antonia Mey, Hannah Pollak, Rafał Szabla
{"title":"数据驱动化学导论课程材料","authors":"J. Cumby, M. Degiacomi, V. Erastova, J. Güven, C. Hobday, Antonia Mey, Hannah Pollak, Rafał Szabla","doi":"10.21105/jose.00192","DOIUrl":null,"url":null,"abstract":"Data-Driven Chemistry is a course aimed at undergraduate students in chemistry with no prior knowledge of programming and programmatic data analysis. It is designed as a 10-week-long course,1 introducing Python programming and its usage in data analysis typically required for a chemistry degree. The course consists of 10 units designed to be used in a blended learning environment of live coding and explanations, followed by a set of in-course tasks to be solved individually or through pair programming.","PeriodicalId":75094,"journal":{"name":"The Journal of open source education","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Course Materials for an Introduction to Data-Driven Chemistry\",\"authors\":\"J. Cumby, M. Degiacomi, V. Erastova, J. Güven, C. Hobday, Antonia Mey, Hannah Pollak, Rafał Szabla\",\"doi\":\"10.21105/jose.00192\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data-Driven Chemistry is a course aimed at undergraduate students in chemistry with no prior knowledge of programming and programmatic data analysis. It is designed as a 10-week-long course,1 introducing Python programming and its usage in data analysis typically required for a chemistry degree. The course consists of 10 units designed to be used in a blended learning environment of live coding and explanations, followed by a set of in-course tasks to be solved individually or through pair programming.\",\"PeriodicalId\":75094,\"journal\":{\"name\":\"The Journal of open source education\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of open source education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21105/jose.00192\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of open source education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21105/jose.00192","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Course Materials for an Introduction to Data-Driven Chemistry
Data-Driven Chemistry is a course aimed at undergraduate students in chemistry with no prior knowledge of programming and programmatic data analysis. It is designed as a 10-week-long course,1 introducing Python programming and its usage in data analysis typically required for a chemistry degree. The course consists of 10 units designed to be used in a blended learning environment of live coding and explanations, followed by a set of in-course tasks to be solved individually or through pair programming.
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