Suppose our goal is to educate the new generation of data scientists working on machine learning and artificial intelligence problems, and especially those who are not intimidated by learning new computing technologies. Where do we start their education at the college level? Given we can't cram everything they need to know into a single introductory course, which topics do we cover in their first course, and which topics do we postpone till later? In this talk, we propose an introductory data science course that places a heavy emphasis on exploratory data analysis and modeling as well as collaboration, effective communication of findings, and ethical considerations as a welcoming and horizon broadening introduction to the discipline at large.
This talk was presented at the IBM CSIG weekly update, see http://cognitive-science.info/community/weekly-update/ for more information on the talk series.