teaching-programming

科目名稱: AI基礎程式設計

• 說明: AI基礎程式設計課程目標在於培養學生邏輯思考能力，透過 Python 程式基礎，引導學生建立邏輯概念、問題分析與解決的能力。

• YouTube課程解說: https://youtu.be/UF55bKYPJ9U

• 課程網址: https://github.com/rwepa/teaching-programming

00_AI基礎程式設計

• 教材: https://github.com/rwepa/teaching-programming/blob/main/00_ai_programming_and_programming.pdf

01_Python語言簡介

• 教材: https://github.com/rwepa/teaching-programming/blob/main/01_python.pdf

02_Anaconda_JupyterNotebook_Spyder簡介

• 教材: https://github.com/rwepa/teaching-programming/blob/main/02_anaconda.pdf

• Jupyter-notebook 加入圖片: https://github.com/rwepa/teaching-programming/blob/main/02_jupyter_insert_image.ipynb

03_資料型別與運算子

• 教材: https://github.com/rwepa/teaching-programming/blob/main/03_type_operator.py

04_資料物件

• 教材: https://github.com/rwepa/teaching-programming/blob/main/04_data_object.py

05_使用NumPy模組與reshape應用

• 教材: https://github.com/rwepa/teaching-programming/blob/main/05_numpy_and_reshape.py

06_判斷式與迴圈應用

• 教材: https://github.com/rwepa/teaching-programming/blob/main/06_if_and_loop.py

07_函數與類別應用

• 教材: https://github.com/rwepa/teaching-programming/blob/main/07_def_and_class.py

08_scipy模組_微積分,內插法 [*]

• 教材: https://github.com/rwepa/teaching-programming/blob/main/08_scipy_calculus_interpolation.py

• pdf 教材: https://github.com/rwepa/teaching-programming/blob/main/08_scipy_calculus_interpolation.pdf

09_pandas模組_開放資料輸入與處理

• 教材: https://github.com/rwepa/teaching-programming/blob/main/09_pandas.py

10_pandas模組_資料視覺化

• 線上說明: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.html

• 教材: https://github.com/rwepa/teaching-programming/blob/main/10_pandas_visualization.py

11_matplotlib模組_資料視覺化

• 教材: https://github.com/rwepa/teaching-programming/blob/main/11_matplotlib_visualization.py

12_seaborn模組_資料視覺化

• 教材: https://github.com/rwepa/teaching-programming/blob/main/12_seaborn_visualization.py

13_Python_Excel_自動化資料分析應

• openpyxl 官網: https://openpyxl.readthedocs.io/en/stable/

• openpyxl 教學: https://realpython.com/openpyxl-excel-spreadsheets-python/

14_streamlit模組_互動式網頁應用

• YouTube: https://youtu.be/FW-dl-flLvk

• 【記得按 讚、訂閱、開啟小鈴鐺】

• Cloud 佈署成果: https://rwepahello.streamlit.app/

• Community Cloud(包括免費版本): https://streamlit.io/cloud

• LINK: https://rwepa.blogspot.com/2023/01/python-streamlit-dashboard.html

• Code: https://github.com/rwepa/teaching-streamlit

15_水資源案例應用

• Water Quality Prediction (7 model) 包括視覺化分析與預測模型

• 7 model: Logistic Regression, Decision Tree, Random Forest, XGBoost, KNN, SVM, AdaBoos

• 反應變數: Potability {1: Potable, 0: Not potable}

• 資料筆數: 3276*10

• water_potability.csv下載: https://github.com/rwepa/DataDemo/blob/master/water_potability.csv

• https://www.kaggle.com/code/imakash3011/water-quality-prediction-7-model/notebook

16_氣候案例應用

• Climate Change: Earth Surface Temperature Data

• ZIP 檔案84.7MB

• 包括 GlobalLandTemperaturesByCity.csv 等5個 csv 檔案

• GlobalLandTemperaturesByCity.csv: 8,599,212*7

• GlobalLandTemperaturesByCity.csv 欄位名稱: dt,AverageTemperature,AverageTemperatureUncertainty,City,Country,Latitude,Longitude

• https://www.kaggle.com/datasets/berkeleyearth/climate-change-earth-surface-temperature-data

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