Fundamentals of Business Data Analytics: Python (I)
Instructor
YU KYUNGHWA
Credit
3.0
Course Type
Elective
Prerequisite
Course Objective
Course Description
Course Schedule
* This schedule is temporary and subject to change.
週次
Week
課程主題
Topic
課程內容與指定閱讀
Content and Reading Assignment
教學活動與作業
Teaching Activities and Homework
學習投入時間
Student workload expectation
課堂講授
In-class Hours
課程前後
Outside-of-class Hours
1
Install JupyterLab
Introduction to Python
(bring your laptop)
Teacher's materials
In class
3
1
2
Expression
Teacher's materials
In class
3
3
3
Loops and Range
Teacher's materials
In class
3
3
4
Function
Teacher's materials
In class
3
3
5
Strings
Teacher's materials
In class
3
3
6
Strings
Conditional Statement
Teacher's materials
In class
3
3
7
Lists
Teacher's materials
In class
3
3
8
Tuples, Set, and Bool
Teacher's materials
In class
3
3
9
Dictionary
Teacher's materials
In class
3
3
10
Numpy
Teacher's materials
In class
3
3
11
Numpy
Teacher's materials
In class
3
3
12
Pandas
Teacher's materials
In class
3
3
13
Pandas
Teacher's materials
In class
3
3
14
Pandas
Teacher's materials
In class
3
3
15
Seaborn
Teacher's materials
In class
3
3
16
Final Exam
Teacher's materials
In class
3
3
Teaching Methods
Teaching Assistant
To be announced
Requirement/Grading
Quiz
50%
Final Exam
40%
Homework
Class participation and others
10%
Important Notes:
1. Participation
Students absent from a class more than three times will receive a “Fail” without notification.
2. Small Quiz
This class does not have a mid-term exam. Instead, a small written quiz or coding exam will be provided for about 20 minutes at the beginning of each class. Questions will be based on the materials taught the previous week.
3. Final exam
The final exam for the Python coding.
< Important Notice >
Students are required to bring their laptops to the first class, as we will install Anaconda (including JupyterLab) and other necessary packages. Students will use their own laptops in every class.
The final exam will be held on the evening of December 18 or 19, depending on classroom availability. The exact date will be announced soon.
Textbook & Reference
1. Course materials will be distributed before each topic begins.
2. Students can find helpful information and lectures on Coursera, edX, or any YouTube channel in their language.
3. Any books in your language help you learn Python.