Please register for the CAUSE webinar : What should we teach in data science courses?
Speaker : Dennis Sun (Cal Poly and Google)
Date and Time : Tuesday, February 13 , 2018 - 2:00pm
Abstract : Over the last few years, there has been a consensus that data science students
should be involved in all stages of the data analysis process, from data preparation and
wrangling, to presentation and visualization. But data science courses have varied widely
in their implementation. Some courses go into great depth about statistical models and
machine learning, while others focus on tools like XML, SQL, and web scraping. While there
is no question that a budding data scientist must acquire these skills eventually, what
should be covered in a course on data science? I suggest that data science courses be
organized around three core concepts: paradigms for representing data, paradigms for
manipulating data, and paradigms for visualization. These are topics of genuine
intellectual merit that are underrepresented elsewhere in the statistics and computer
science curriculum. The tools are secondary, and I suggest how such a course could be
taught using R examples using the tidyverse or using Python examples
Registration Link : [
https://www.causeweb.org/cause/webinar/teaching/2018-02-13 |
https://www.causeweb.org/cause/webinar/teaching/2018-02-13 ]
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