✳flâneur — a map of the web's best reading

CSC 151 - A computer scientist's perspective on data science

eikmeier.sites.grinnell.edu · 1,357 words · saved by 1 readers

Although the field of data science is rapidly gaining in popularity, its definition is tenuous, at best. As one of the statistics faculty noted when talking to us about possible ways to design a data science curriculum, “if you ask a dozen statisticians to define data science, you’ll get at least a half-dozen different answers”. In this course, we take an algorithmic approach to data science. Let’s consider what we mean by that. Data science, like statistics, is a way of exploring sets of information. Data science distinguishes itself from statistics by focusing more on providing a wide variety of mechanisms for gaining potential insights from existing data sets. In addition, to a computer scientist, data science is an opportunity to think about a progression of ways to work with data. For example, here is an “algorithmic” data science pipeline: Starting with a data set that is typically in a somewhat unstructured, less-than-usable form, one wrangles the data into a usable form, cleans

CSC 151 - A computer scientist's perspective on data science A computer scientist's perspective on data science Due Monday, 3 November 2025 --> Summary The subject of this course is “data science”. But what is data science, anyway? We consider some perspectives, particularly the algorithmic perspective we emphasize in this course. What is data science? Although the field of data science is rapidly gaining in popularity, its definition is tenuous, at best. As one of the statistics faculty noted when talking to us about possible ways to design a data science curriculum, “if you ask a dozen stati

Explore this link on the map →

saved by

related reading