This course consists of two parts:
1. This course will focus on using Python for data analysis:
i. Introducing essential Python libraries: Numpy, Pandas, Scikit-learn, and Matplotlib.
ii. Introducing manipulating, processing, cleaning, and crunching data in Panadas. Also, we will discuss using Panadas for time series data analysis, such as financial data.
2. We will introduce using Scikit-learn for supervised learning and unsupervised learning.
i. supervised learning: linear regression, logistic regression, decision trees,
unsupervised learning: K-means.

一、Course Introduction	This course consists of two parts: 1. This course will focus on using Python for data analysis: i. Introducing essential Python libraries: Numpy, Pandas, Scikit-learn, and Matplotlib. ii. Introducing manipulating, processing, cleaning, and crunching data in Panadas. Also, we will discuss using Panadas for time series data analysis, such as financial data. 2. We will introduce using Scikit-learn for supervised learning and unsupervised learning. i. supervised learning: linear regression, logistic regression, decision trees, unsupervised learning: K-means.
二、Document of syllabus	Program Syllabus (Big Data Analysis with Python (I)).pdf
三、教材編選	Self Developed	Lecture Handout	Self Edited Textbooks	Teaching Program	Self Made Teaching Video	Other
四、教學教法	Lecture Slides	Group Discussion	Student Oral Report	Problem Based Learning	Case Study	Other
五、評量工具	Mid-Term Exam	Final Exam	Quiz	Assignment	Homework	Mid-Term Report	Final Report
五、評量工具	Project Report	Evaluation Ruler	Other
Please respect to the intellectual property rights, do not photocopy the textbooks which assigned by professors.