課程資訊
課程名稱
Python資料分析與機器學習應用
Data Analysis and Machine Learning with Python 
開課學期
111-2 
授課對象
 
授課教師
何承遠 
課號
IM1013 
課程識別碼
705E14200 
班次
03 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期二2,3,4(9:10~12:10) 
上課地點
管一B01 
備註
本課程以英語授課。自備筆電。For non-EE and non-CS students.兼通識A6*。。A6*:量化分析與數學素養領域。可充抵通識
總人數上限:80人 
 
課程簡介影片
 
核心能力關聯
核心能力與課程規劃關聯圖
課程大綱
為確保您我的權利,請尊重智慧財產權及不得非法影印
課程概述

Mar. 3, 2023 updated
Some students dropped the course and/or applications, so we accepted all add and audit applications.
However, some students gave us the wrong emails, so these students cannot get registered code (for add course) or audit invitation letter (for audit).
If you who applied the form didn't get the code or invitation letter and still have an interest in this course, please contact TAs directly today.
Note that we DO NOT accept the new applications.

由於有些同學退選課程或是取消申請加簽,所以最後我們全簽了所有加簽和旁聽申請。
然而,有少數同學留了錯誤的email信箱,所以這些同學將無法收到加簽碼(想加簽的)或旁聽邀請信(想旁聽的)。
假如曾填過申請單的你沒收到加簽碼或邀請信,但仍然對本課程有興趣的,請直接聯絡助教。
注意:我們不再接受新的加簽與旁聽申請。


Feb. 28, 2023 updated
If the answer of your question can be found in the course outline, recorded videos of classes, and materials I provided, I won't reply the email and answer your question.
Before you ask a question, please try your best to find the answer and think about whether your question is suitable for asking or not.

Feb. 25, 2023 updated
English version
The latest statistics on enrollment are as follows:
Class No 01 02 03 04
Classroom capacity 120 120 120 120
Course selection system 57 52 53 52
Add application 92 78 49 55
Audit application 21 17 4 17
According to the instructions during the first class, no more add applications will be accepted from Feb. 25 to Mar. 4.
However, the students who have applied for add course and are worried about not being selected can send an email to inform the teacher and teaching assistants of which class they would like to switch to if there are available spots.
(Please send the email to both the teacher and teaching assistants).

中文版
最新人數統計如下:
班次 01 02 03 04
教室上限人數 120 120 120 120
選課系統人數 57 52 53 52
申請加簽人數 92 78 49 55
申請旁聽人數 21 17 4 17
按照第一堂課與同學的說明,從2/25~3/4不再接受新的加簽申請。
但有申請過加簽的同學,假如擔心自己沒被抽中,可以來信告知想換到哪個尚未額滿的班級。
(寄信時請寄給老師和助教們)


Feb. 20, 2023 updated
add recorded video list of today's class and video list of Python last semester into the Final Course Outline.
after the end of course add and drop, these documents and video lists will be moved to NTU Cool

Feb. 19, 2023 updated
Final Course Outline (is moved to NTU Cool)


Jan. 9, 2023 updated
1. About online, e-learning, live streaming, and recorded video
There are no online classes, e-learning materials, live streaming, and recorded video in this course, right now.

2. About extending number of student for adding course
You must come to the class in the first week. Otherwise, you cannot be added into the course.
The max number of all students is 120, the capacity of B01, Building 1, College of Management.
If the number is larger than 120, the priority for adding course is as follows.
a. fourth grade and above
b. others (random selection)

3. We use midterm and final projects rather than midterm and final tests.
Furthermore, the results of midterm project is the input data for the final project.

----------------------------------------------------------------------------------
This course will be your guide to learning how to use the power of Python to analyze data and use powerful machine learning algorithms, and then create beautiful visualizations for the analysis results and predictions.
This course is designed for beginners with some programming experience, the guys who already know some Python and are ready to dive deeper into using those Python skills for data analysis and Machine Learning, or experienced developers looking to make the jump to Data Science.
I want to help guide students to learning a set of skills to make them extremely hirable in today's workplace environment. Therefore, I'll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Enroll in the course and become a data scientist! 

課程目標
1. Use Python for Data Analysis and Machine Learning
2. Understand how to Use Tools to Analyze Data
3. Understand how to Use Existing Machine Learning Modules/Packages
4. Learn Related Modules and Tools in Python, like NumPy, Pandas, Matplotlib, and SciKit-Learn 
課程要求
Take Python programming or related course before, or understand Python 
預期每週課後學習時數
 
Office Hours
另約時間 
指定閱讀
No 
參考書目
1. Introduction to Machine Learning with Python: A Guide for Data Scientists
2. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
3. Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning
4. Python Cookbook
5. Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts,Tools, and Techniques to Build Intelligent Systems 
評量方式
(僅供參考)
   
針對學生困難提供學生調整方式
 
上課形式
提供學生彈性出席課程方式
作業繳交方式
團體報告取代個人報告
考試形式
其他
由師生雙方議定
課程進度
週次
日期
單元主題
Week 1
2/21  Course Overview, What is Data Analysis, What is Machine Learning 
Week 2
2/28  228 holidays 
Week 3
3/07  Steps and Flows in Data Analysis, Introduction to Pandas
Functions and Module in Pandas 
Week 4
3/14  Machine Learning: Supervised vs Unsupervised vs Reinforcement Learning
Grouping due 
Week 5
3/21  Algorithms and Modules in Supervised Machine Learning I 
Week 6
3/28  Homework 1 Presentation
Algorithms and Modules in Supervised Machine Learning II 
Week 7
4/04  Ching Ming holidays 
Week 8
4/11  Midterm Project Presentation 
Week 9
4/18  Algorithms and Modules in Unsupervised Machine Learning 
Week 10
4/25  Data Modeling, Tuning, and Explanation (by Manual) 
Week 11
5/02  Data Modeling, Tuning, and Explanation (by Automatic and Functions) 
Week 12
5/09  Homework 2 Presentation
Implementation and Discussion 
Week 13
5/16  Case Study: Energy Saving and Product Defect Detection 
Week 14
5/23  Case Study: Prognostics and Health Management (PHM) 
Week 15
5/30  Lecture/Talk (topic: TBD) 
Week 16
6/06  Final Project Presentation