开始时间: 04/22/2022 持续时间: 3 weeks
所在平台: EdxArchive 课程类别: 其他类别 大学或机构: UTArlingtonX 授课老师: Andrew E. Krumm |
课程主页: https://www.edx.org/archive/feature-engineering-improving-learning-utarlingtonx-link-la-fex
课程评论:没有评论
How can data-intensive research methods be used to create more equitable and effective learning environments? In this course, you will learn how data from digital learning environments and administrative data systems can be used to help better understand relevant learning environments, identify students in need of support, and assess changes made to learning environments.
This course pays particular attention to the ways in which researchers and data scientists can transform raw data into features (i.e., variables or predictors) used in various machine learning algorithms. We will provide strategies for using prior research, knowledge from practice, and logic to create features, as well as build and evaluate machine learning models. The process of building features will be discussed within a broader data-intensive research workflow using R.