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# 使用指南
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本指南提供了使用「初學者的數據科學」課程的範例和常見工作流程。
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## 目錄
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- [如何使用此課程](../..)
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- [使用課程](../..)
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- [使用 Jupyter Notebook](../..)
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- [使用測驗應用程式](../..)
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- [常見工作流程](../..)
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- [自學者的提示](../..)
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- [教師的提示](../..)
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## 如何使用此課程
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此課程設計靈活，可用於多種方式：
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- **自學**：按照自己的速度獨立完成課程
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- **課堂教學**：作為結構化課程進行指導教學
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- **學習小組**：與同伴合作學習
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- **工作坊形式**：密集的短期學習課程
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## 使用課程
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每節課遵循一致的結構以最大化學習效果：
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### 課程結構
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1. **課前測驗**：測試現有知識
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2. **手繪筆記**（可選）：關鍵概念的視覺摘要
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3. **影片**（可選）：補充的影片內容
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4. **書面課程**：核心概念和解釋
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5. **Jupyter Notebook**：動手編碼練習
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6. **作業**：練習所學內容
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7. **課後測驗**：加強理解
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### 課程範例工作流程
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```bash
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# 1. Navigate to the lesson directory
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cd 1-Introduction/01-defining-data-science
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# 2. Read the README.md
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# Open README.md in your browser or editor
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# 3. Take the pre-lesson quiz
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# Click the quiz link in the README
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# 4. Open the Jupyter notebook (if available)
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jupyter notebook
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# 5. Complete the exercises in the notebook
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# 6. Work on the assignment
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# 7. Take the post-lesson quiz
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```
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## 使用 Jupyter Notebook
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### 啟動 Jupyter
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```bash
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# Activate your virtual environment
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source venv/bin/activate # On macOS/Linux
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# OR
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venv\Scripts\activate # On Windows
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# Start Jupyter from the repository root
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jupyter notebook
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```
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### 執行 Notebook 的單元格
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1. **執行單元格**：按 `Shift + Enter` 或點擊「執行」按鈕
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2. **執行所有單元格**：選擇「Cell」→「Run All」選項
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3. **重啟核心**：如果遇到問題，選擇「Kernel」→「Restart」
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### 範例：在 Notebook 中處理數據
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```python
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# Import required libraries
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import pandas as pd
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import numpy as np
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import matplotlib.pyplot as plt
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# Load a dataset
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df = pd.read_csv('data/sample.csv')
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# Explore the data
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df.head()
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df.info()
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df.describe()
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# Create a visualization
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plt.figure(figsize=(10, 6))
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plt.plot(df['column_name'])
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plt.title('Sample Visualization')
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plt.xlabel('X-axis Label')
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plt.ylabel('Y-axis Label')
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plt.show()
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```
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### 保存您的工作
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- Jupyter 會定期自動保存
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- 手動保存：按 `Ctrl + S`（macOS 上為 `Cmd + S`）
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- 您的進度會保存到 `.ipynb` 文件中
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## 使用測驗應用程式
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### 本地運行測驗應用程式
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```bash
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# Navigate to quiz app directory
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cd quiz-app
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# Start the development server
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npm run serve
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# Access at http://localhost:8080
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```
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### 進行測驗
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1. 課前測驗位於每節課的頂部
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2. 課後測驗位於每節課的底部
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3. 每個測驗包含 3 個問題
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4. 測驗旨在加強學習，而非全面測試
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### 測驗編號
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- 測驗編號為 0-39（共 40 個測驗）
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- 每節課通常有課前和課後測驗
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- 測驗 URL 包含測驗編號：`https://ff-quizzes.netlify.app/en/ds/quiz/0`
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## 常見工作流程
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### 工作流程 1：完全初學者路徑
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```bash
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# 1. Set up your environment (see INSTALLATION.md)
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# 2. Start with Lesson 1
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cd 1-Introduction/01-defining-data-science
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# 3. For each lesson:
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# - Take pre-lesson quiz
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# - Read the lesson content
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# - Work through the notebook
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# - Complete the assignment
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# - Take post-lesson quiz
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# 4. Progress through all 20 lessons sequentially
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```
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### 工作流程 2：特定主題學習
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如果您對某個特定主題感興趣：
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```bash
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# Example: Focus on Data Visualization
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cd 3-Data-Visualization
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# Explore lessons 9-13:
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# - Lesson 9: Visualizing Quantities
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# - Lesson 10: Visualizing Distributions
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# - Lesson 11: Visualizing Proportions
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# - Lesson 12: Visualizing Relationships
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# - Lesson 13: Meaningful Visualizations
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```
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### 工作流程 3：基於項目的學習
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```bash
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# 1. Review the Data Science Lifecycle lessons (14-16)
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cd 4-Data-Science-Lifecycle
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# 2. Work through a real-world example (Lesson 20)
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cd ../6-Data-Science-In-Wild/20-Real-World-Examples
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# 3. Apply concepts to your own project
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```
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### 工作流程 4：基於雲端的數據科學
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```bash
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# Learn about cloud data science (Lessons 17-19)
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cd 5-Data-Science-In-Cloud
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# 17: Introduction to Cloud Data Science
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# 18: Low-Code ML Tools
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# 19: Azure Machine Learning Studio
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```
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## 自學者的提示
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### 保持有條理
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```bash
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# Create a learning journal
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mkdir my-learning-journal
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# For each lesson, create notes
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echo "# Lesson 1 Notes" > my-learning-journal/lesson-01-notes.md
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```
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### 定期練習
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- 每天或每週安排固定的學習時間
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- 每週至少完成一節課
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- 定期回顧之前的課程
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### 與社群互動
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- 加入 [Discord 社群](https://aka.ms/ds4beginners/discord)
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- 參與 Discord 的 #Data-Science-for-Beginners 頻道 [Discord 討論](https://aka.ms/ds4beginners/discord)
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- 分享您的進度並提出問題
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### 建立自己的項目
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完成課程後，將概念應用於個人項目：
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```python
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# Example: Analyze your own dataset
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import pandas as pd
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# Load your own data
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my_data = pd.read_csv('my-project/data.csv')
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# Apply techniques learned
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# - Data cleaning (Lesson 8)
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# - Exploratory data analysis (Lesson 7)
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# - Visualization (Lessons 9-13)
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# - Analysis (Lesson 15)
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```
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## 教師的提示
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### 課堂設置
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1. 查看 [for-teachers.md](for-teachers.md) 以獲取詳細指導
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2. 設置共享環境（GitHub Classroom 或 Codespaces）
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3. 建立溝通渠道（Discord、Slack 或 Teams）
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### 課程規劃
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**建議的 10 週計劃：**
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- **第 1-2 週**：介紹（課程 1-4）
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- **第 3-4 週**：數據處理（課程 5-8）
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- **第 5-6 週**：數據可視化（課程 9-13）
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- **第 7-8 週**：數據科學生命周期（課程 14-16）
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- **第 9 週**：雲端數據科學（課程 17-19）
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- **第 10 週**：實際應用與最終項目（課程 20）
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### 運行 Docsify 以離線訪問
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```bash
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# Serve documentation locally for classroom use
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docsify serve
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# Students can access at localhost:3000
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# No internet required after initial setup
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```
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### 作業評分
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- 查看學生 Notebook 中完成的練習
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- 通過測驗分數檢查理解程度
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- 使用數據科學生命周期原則評估最終項目
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### 創建作業
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```python
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# Example custom assignment template
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"""
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Assignment: [Topic]
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Objective: [Learning goal]
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Dataset: [Provide or have students find one]
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Tasks:
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1. Load and explore the dataset
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2. Clean and prepare the data
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3. Create at least 3 visualizations
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4. Perform analysis
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5. Communicate findings
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Deliverables:
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- Jupyter notebook with code and explanations
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- Written summary of findings
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"""
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```
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## 離線使用
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### 下載資源
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```bash
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# Clone the entire repository
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git clone https://github.com/microsoft/Data-Science-For-Beginners.git
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# Download datasets in advance
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# Most datasets are included in the repository
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```
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### 本地運行文檔
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```bash
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# Serve with Docsify
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docsify serve
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# Access at localhost:3000
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```
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### 本地運行測驗應用程式
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```bash
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cd quiz-app
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npm run serve
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```
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## 訪問翻譯內容
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翻譯版本提供超過 40 種語言：
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```bash
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# Access translated lessons
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cd translations/fr # French
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cd translations/es # Spanish
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cd translations/de # German
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# ... and many more
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```
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每個翻譯版本的結構與英文版保持一致。
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## 其他資源
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### 繼續學習
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- [Microsoft Learn](https://docs.microsoft.com/learn/) - 額外的學習路徑
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- [Student Hub](https://docs.microsoft.com/learn/student-hub) - 學生資源
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- [Azure AI Foundry](https://aka.ms/foundry/forum) - 社群論壇
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### 相關課程
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- [AI for Beginners](https://aka.ms/ai-beginners)
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- [ML for Beginners](https://aka.ms/ml-beginners)
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- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
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- [Generative AI for Beginners](https://aka.ms/genai-beginners)
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## 獲取幫助
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- 查看 [TROUBLESHOOTING.md](TROUBLESHOOTING.md) 以解決常見問題
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- 搜索 [GitHub Issues](https://github.com/microsoft/Data-Science-For-Beginners/issues)
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- 加入我們的 [Discord](https://aka.ms/ds4beginners/discord)
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- 查看 [CONTRIBUTING.md](CONTRIBUTING.md) 以報告問題或貢獻內容
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---
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**免責聲明**：
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本文件已使用 AI 翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。儘管我們努力確保翻譯的準確性，但請注意，自動翻譯可能包含錯誤或不準確之處。原始文件的母語版本應被視為權威來源。對於關鍵信息，建議使用專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或誤釋不承擔責任。 |
