Software Development Essentials

[SW-3] 學習建議：搭配 [SW-1-Ref-1] 「Chapter 2 系統操作」章節，熟悉基本的 Linux 與 Shell 指令後，再進入 [SW-3A] 課程，系統化學習 Bash 腳本語言的結構與應用，強化資料與檔案處理能力。。

[SW-3A]
Introduction to Bash Scripting ・ DataCamp ・ 4 Hours Course

Bash is a concise, superfast, and robust scripting language for data and file manipulation. It’s a vital skill for building analytics pipelines in the cloud, favored by Linux users to work with data stored across multiple files.

In this course, we’ll guide you through the basics of Bash scripting. We begin with an introduction to Bash script structures, including inputting arguments and outputting results. You’ll then work through data structures, such as variables and arrays, and control statements, including loops and conditionals. You’ll then put what you’ve learned into practice, by creating your own Bash functions and scheduling automated scripts to run like clockwork with cron.

[SW-4] 學習建議：搭配 [SW-1-Ref-1] 「Chapter 3 程式碼閱讀、除錯、追蹤與分析」章節，進行 [SW-4A] 實作課程，透過錯誤排查練習，學習程式偵錯技巧 。

[SW-4A]
Debugging Code ・ DataCamp ・ Hands-on Project

Sharpen your debugging skills to enhance sales data accuracy. 

Debugging code is an essential skill for a data analyst, encompassing reading error messages and handling exceptions. In this project, you will apply your debugging skills to enhance some code used by a company to analyze sales data. You will need to modify the code to handle exceptions caused by missing or incorrect data entries.

[SW-5] 學習建議：搭配 [SW-1-Ref-1] 「Chapter 4 多人協作開發」章節，完成 [SW-5A]，即可開始使用 GitHub 進行版本控制與基本協作。若需進一步了解 Git 操作細節與工作流程，再補充學習 [SW-5B]。

[SW-6] 學習建議：完成 [SW-6A]，學習如何以 Python 進行探索性資料分析 (Exploratory Data Analysis, EDA)，熟悉常見的資料檢視、清理、洞察與視覺化方法，為後續的資料建模與溝通分析打下基礎。

[SW-6A]
Exploratory Data Analysis in Python・DataCamp・4 hours course

Learn how to explore, visualize, and extract insights from data using exploratory data analysis (EDA) in Python.

[SW-7] 學習建議：先完成 [SW-7A]，建立資料視覺化的基本觀念與 Seaborn 操作技巧；若已具備基礎並希望進一步掌握進階圖表與美化技巧，可選讀 [SW-7B] 強化應用能力。