課程大綱
電子書
電子書網址：https://bookdown.org/tpemartin/ntpu-programming-for-data-science/
電子書加個人註記：https://via.hypothes.is/https://bookdown.org/tpemartin/ntpu-programming-for-data-science/
課程進度網頁
Course Objectives
This course is to build the foundation for being a data scientist–who masters both data analysis and data engineering. There are two programming languages that will be taught through the course: R and Javascript. R will serve as the data analysis backend, while Javascipt will serve as the communication tool interacting with cloud services–such as Google G Suite. After taking the course, students will be able to create their own data services that can automate routine works and enhance their productivities. (The course will be taught mainly in English which is an important skill for being a good programmer.)
本課程是成為資料科學家的基礎課程。課程設計會使用R語言來當做資料處理工具，同時也會教授Javascript來衘接與雲端服務的資訊互動（如Google G Suite）。 認真學完本課程的學生將俱備有能將日常例行工作自動化的創造能力。由於英語是程式語言的主要寫作與溝通工具，本課程多數時候為英語授課。
林茂廷老師
107學年
Assesment
作業：15%
期中考：35%
期末考：40%
課堂GitHub commits：10%
Before you start
Before your start, please do the following:
Register a Gmail.
Install Google Chrome.
Register a GitHub account, then install Github Desktop.
Register a Gitter account using your GitHub account.
Sign up Gitter chat room of this course.
Sign up a Hypothes.is account.
Join course Hypothes.is group (click to join).
Install Hypothes.is Chrome extension
Fill in your account information in 學生資訊帳號單.
GitHub in-class practice repo
https://github.com/tpemartin/107-2-inclass-practice
Students
- Fill in your in-class practice repo information in: 資料科學入門GitHub課堂練習repo回填表單
Teacher
During the class I will constantly update my in-class demo in the following repo: https://github.com/tpemartin/ProgrammingForDataScience-Practice
平時成績
看公告加分、課堂練習成績、作業成績都放在 平時成績Google Sheets
Setup chunk
library(readr); library(dplyr); library(stringr); library(lubridate)