106學年第1學期課程綱要

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一、課程基本資料
開課序號 1554 課程學制
科目代碼 ENC2055 課程名稱 程式語言用於語言分析之導論
英文名稱 Introduction to Programming Languages for Linguistic Analysis
全/半年 必/選修 選修
學分數 3.0 每週授課時數 正課時數: 3 小時
開課系級 英語系(碩)碩博合開
先修課程
課程簡介 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 use the language R as our featuring programming language and introduce you to R, Rstudio, and a collection of R packages designed to work together to make linguistic analyses fast, fluent, and fun. 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.
課程目標 對應系所核心能力
1. Gain the fundamental concepts in programming languages 碩士:
 1-1 具備深化專業知識範疇及其學術研究之能力
 2-3 具有運用多媒體及資訊科技之能力
 3-2 具有獨立思考、發掘問題及批判之能力
2. Demonstrate the ability to write scripts to analyze linguistic data 碩士:
 1-1 具備深化專業知識範疇及其學術研究之能力
 2-3 具有運用多媒體及資訊科技之能力
 3-2 具有獨立思考、發掘問題及批判之能力

二、教學大綱
授課教師 甯俐馨
教學進度與主題

Week1: Course overview; Basic Unix commands

 

Week2: Shell scripting

 

Week3: Shell scripting

 

Week4: Python's data structure - lists, tuples, dictionaries, strings

 

Week5: Holiday (Made-up class on 9/30) Python's data structure - lists, tuples, dictionaries, strings

 

Week6: Python for data analysis - numpy and pandas

 

Week7: Python for data analysis - numpy and pandas

 

Week8: Python for data visualization - matplotlib

 

Week9: Python for data visualization - matplotlib

 

Week10: Midterm exam 

 

Week11: Python for natural language processing

 

Week12: R's data structure and basic function

 

Week13: R for data visualization -- basic function, lattice, and ggplot2

 

Week14: R for data visualization -- basic function, lattice, and ggplot2

 

Week15: R for predicative analysis (regression)

 

Week16: R for data mining 

 

Week17: Holiday

 

Week18: Final exam

教學方法
方式 說明
講述法  
問題解決教學  
實驗/實作  
評量方法
方式 百分比 說明
作業 40 %  
期中考 20 %  
期末考 20 %  
課堂討論參與 10 %  
出席 10 %  
參考書目

Recommended textbook: 

 

Jerry Peek. Unix Power Tools

Mark Lutz. LearningPython.

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