One of the biggest pain points for both teachers and learners of data science in R is navigating the often unspoken prerequisite skills and content knowledge necessary to successfully apply R to data science problems. In this talk, R for data science educators will learn actionable strategies to more effectively bring learners up to speed, while learners will develop strategies to identify and address their own knowledge gaps.
By incorporating learnings from the establishment of a data-driven culture at Teaching Trust, coupled with her experience creating and leading the R for Data Science Online Learning Community, Jesse will share strategies that can be immediately implemented with groups of any size in order to more quickly develop data science skills in R. These include methods for identifying individual gaps in knowledge, establishing mentor and learner relationships, incorporating best practices from the field of education, and bolstering fundamental computer science skills.
- Posted on:
- February 10, 2018
- 1 minute read, 149 words
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