Last Updated on: 2023-02-22
Important course information will be posted on this web page and announced in class. You are responsible for all material that appears here and should check this page for updates frequently.
The objective of this course is to provide a comprehensive introduction to programming languages with a special focus on its application in linguistic analyses. This course is especially tailored to those who do not have any background or experiences in coding. We will start from the very basic concepts, such as data types, variable assignments, control structures, to more complex procedures such as routines, functions, and other exploratory project-based tasks. The course consists of a series of theme-based hands-on tutorials, which demonstrate how the flexibility of the programming language can help you become a more efficient and productive data scientist.
Specifically, this course will cover coding skills for basic text analytics, including R, Python and shell scripting basics, with the language R being our featuring programming language. We will introduce you to R, Rstudio, and a collection of R packages designed to work together to make linguistic analyses fast, fluent, and fun. Furthermore, we will show you how you can make use of the integrated RStuido for Python and shell scripting. By the end of the course, students should have a working knowledge of coding and an initial ability to advance a project independently as a data scientist.
(This schedule is tentative and subject to change. Please pay attention to the announcements made during the class.)
|Data Science and R
|Code Format Convention, Subsetting
|Conditions and Loops
|Data IO and Iteration
|Data IO and Iteration
|Data Analysis and Text Analytics: A Primer
All the course materials are available on the course website. Please consult the instructor for the direct link to the course materials. They will be provided as a series of online packets (i.e., handouts, script source codes etc.) on the course website. These teaching materials are based on the following recommended readings.
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