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Interleaving Computational and Inferential Thinking: Data Science for Undergraduates at Berkeley
arXiv - CS - Computers and Society Pub Date : 2021-02-13 , DOI: arxiv-2102.09391
Ani Adhikari, John DeNero, Michael I. Jordan

The undergraduate data science curriculum at the University of California, Berkeley is anchored in five new courses that emphasize computational thinking, inferential thinking, and working on real-world problems. We believe that interleaving these elements within our core courses is essential to preparing students to engage in data-driven inquiry at the scale that contemporary scientific and industrial applications demand. This new curriculum is already reshaping the undergraduate experience at Berkeley, where these courses have become some of the most popular on campus and have led to a surging interest in a new undergraduate major and minor program in data science.

中文翻译:

计算和推理思维的交织:伯克利大学本科生的数据科学

加利福尼亚大学伯克利分校的本科数据科学课程以五门新课程为基础,这些课程强调计算思维,推论思维以及解决实际问题。我们认为,将这些要素融入我们的核心课程中对于让学生做好准备,使其能够以当代科学和工业应用所需的规模进行数据驱动的查询至关重要。这项新课程已经重塑了伯克利大学的本科生经验,这些课程已成为校园中最受欢迎的一些课程,并引起了人们对数据科学新的本科专业和副修课程的浓厚兴趣。
更新日期:2021-02-19
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