Why use data from outside sources? The world is awash in data, and whatever else we teach in a data science curriculum, data must be at the center. Calls to modernize statistics and data science courses regularly point to using “real” data. The National Academies Report on Data Science for Undergraduates (see previous blog post at: https://teachdatascience.com/nasem/) reports Data Management & Curation as a core part of data acumen. Indeed, they recognize data provenance to be a key skill which is “important for all students in [a] data science program.
Data Science for Undergraduates As the first entry in this blog, we thought it would be appropriate to begin with the 2018 consensus report “Data Science for Undergraduates: Opportunities and Options”. Nick was a co-author of this National Academies Report and it provides an accessible overview of undergraduate data science courses and programs. Co-chairs of the committee were Laura Haas (University of Massachusetts/Amherst, https://www.cics.umass.edu/faculty/directory/haas-laura) and Al Hero (University of Michigan, https://hero.
Why another Data Science Education blog? This is an exciting time to be teaching students how to extract meaning from data. Amidst the flood of information available in almost all domains there have been a flourishing of powerful, open-source tools to help with the process. For instructors, the many changes can be hard to keep up with. In this blog, we’re hoping to create a roadmap for faculty development that will ease the learning curve and help busy people incorporate new tools and approaches into their teaching.
The NASEM Data Science for Undergraduates report noted that the storage, preparation, and accessing of data is at the heart of data science and that students need to directly experience multiple forms of data, including the use of databases. SQL (pronounced sequel) stands for Structured Query Language; it is a language designed to manage data in a relational database system. The papers https://chance.amstat.org/2015/04/setting-the-stage and https://chance.amstat.org/2015/04/databases/ provide a high level overview of database systems.