Holiday
GEN III綜三315 R7R8R9
本課程之內容包括:Python 語言基礎語法、程式實作、大數據分析、機器學習
Course keywords: python, pandas, sklearn, 大數據big data、機器學習machine learning, 人工智慧artificial intelligence ## 本課程之內容包括:Python語法、程式寫作技巧與觀念及實作範例。延續程式設計一,本課程會用 Pandas套件教導學生分析大數據。除此之外,程式設計二,此課程將探討機器學習(人工智慧)的基礎 概念,並用sklearn來實作。 This course covers Python syntax, programming skills and concepts, and practical examples. Continuing from Programming I, this course will use the Pandas suite to teach students to analyze big data. In addition, programming II, this course will explore the basic concepts of machine learning (artificial intelligence), and implement it with sklearn. ## 指定用書 一行指令學Python:用Pandas掌握商務大數據分析<全華> 一行指令學python 用機器學習掌握人工智慧<全華> ## 教學方式 透過課本解說各主題的實作技巧,由學生練習、測試與完成相關之課堂實作或作業。課本內容錄製於線 上平台、 方便同學課後複習。上課講義同步放置於線上平台。 The textbook explains the practical skills of each topic, and students will practice, test and complete the related classroom practical or assignments. The textbook is recorded on the online platform for students to review after class. Lecture notes are placed on the online platform simultaneously. ## 授課進度及內容(Teaching Schedule & Contents): Week Topic 1 課程介紹Course Introduction 2 Python 語言基本功能Basic Function of Python Language 3 Pandas - Dataframe I 4 Pandas - Dataframe II 5 Pandas -多層級索引鍵 6 Pandas練習 - 系所生源分析 7 Pandas練習 - 業務銷售分析 I 8 Pandas練習 - 業務銷售分析 II 9 期中考Midterm Exam 10 Pandas練習 - 股市分析 11 Pandas練習 - 問卷資料分析 12 Sklearn資料預處理 13 簡單線性迴歸 14 多元線性迴歸 15 決策樹 16 信用偵測 17 文字處理 18 期末考Final Exam ## 學習評量方式(Learning Evaluation Methods): 出席(Attendance): 10 % 期中考(筆試)(Midterm Exam) 30% 期末考(Final Exam) 30% 作業 (Homework) 30%
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19:30b20:20 | |||||
20:30c21:20 |
Average Percentage 84.13
Std. Deviation 8.22
限數學系大學部清班
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