<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Summer Course | Gyumin Lee</title><link>https://gyumin-lee68.github.io/tags/summer-course/</link><atom:link href="https://gyumin-lee68.github.io/tags/summer-course/index.xml" rel="self" type="application/rss+xml"/><description>Summer Course</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 23 Aug 2023 00:00:00 +0000</lastBuildDate><image><url>https://gyumin-lee68.github.io/media/icon_hu7729264130191091259.png</url><title>Summer Course</title><link>https://gyumin-lee68.github.io/tags/summer-course/</link></image><item><title>Machine Learning/AI-Based Research Methodologies in Child and Family Studies</title><link>https://gyumin-lee68.github.io/teaching/23sum_ml/</link><pubDate>Wed, 23 Aug 2023 00:00:00 +0000</pubDate><guid>https://gyumin-lee68.github.io/teaching/23sum_ml/</guid><description>&lt;p>Instructor: Professor Wonkyung Jang (Dept. Instructional Leadership and Academic Curriculum, The University of Oklahoma)&lt;/p>
&lt;p>Textbook: Lecture notes&lt;/p>
&lt;p>Topics: Introduction to Data Science and R Programming (Importance and concepts of data science, Introduction to the R programming language, its basic syntax, and RStudio environment setup.
Understanding data types, variables, and data structures, Overview of data visualization algorithms, Statistical pitfalls in social sciences: Common errors and strategies to avoid them.
Hands-on practice with basic statistical methods (e.g., T-test, ANOVA, Regression) using R), Machine Learning/AI Techniques for Structured and Unstructured Data (Introduction to supervised and unsupervised learning methodologies, Overview of text mining: Text preprocessing and natural language processing techniques.
Hands-on machine learning practice using R, focusing on U.S. child and family studies datasets)&lt;/p>
&lt;p>For Students: Before the first session, it is recommended to install the data science program R (&lt;a href="https://cran.yu.ac.kr/" target="_blank" rel="noopener">https://cran.yu.ac.kr/&lt;/a>) and RStudio (&lt;a href="https://posit.co/download/rstudio-desktop/%29" target="_blank" rel="noopener">https://posit.co/download/rstudio-desktop/)&lt;/a>.&lt;/p>
&lt;p>If you encounter any issues or have further questions, feel free to email me. I will respond as soon as possible.&lt;/p></description></item></channel></rss>