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CS 65 W — Data Analysis with Python

Quarter: Winter
Course Format: Flex Online (About Formats)
Duration: 6 weeks
Date(s): Jan 30—Mar 10
Refund Deadline: Feb 2
Unit: 1
Tuition: $455
Instructor(s): Matt Harrison
Limit: 60
Class Recording Available: Yes
Status: Open
 
DOWNLOAD THE SYLLABUS » (subject to change)
Winter
Flex Online(About Formats)
Date(s)
Jan 30—Mar 10
6 weeks
Refund Date
Feb 2
1 Unit
Fees
$455
Instructor(s):
Matt Harrison
Limit
60
Recording
Yes
Open
DOWNLOAD THE SYLLABUS » (subject to change)
We live in a world surrounded by data. But how do we observe and extract value from this data? How do we explore and begin to understand and visualize large data sets? Are there relationships in the data or unusual observations we can uncover? This course will help students learn how to perform data analysis using Python. We will acquire data, examine it, clean it up, visualize it, and begin to infer conclusions from it. We will walk through the basics of data analysis using the Python toolchain. These popular tools are both open source and very popular among data scientists and analysts in both academia and industry. They include the Jupyter Notebook, pandas, plotting with matplotlib and seaborn, and some basics of machine learning using Scikit-Learn. We will explore categorical data that provides labels such as the make of a car or the web browser of a visitor to a website. We will also discuss charts, tables, and correlations and explore some color theory. Finally, we will dive into numerical data, including how to create, interpret, and plot data with multiple dimensions. Students will leave the course able to analyze a data set from start to finish, providing graphical and numerical summaries, correlations, and outliers.

Students are expected to have some Python programming skills.

MATT HARRISON
Principal Consultant and Corporate Trainer, MetaSnake

Matt Harrison has been using Python since 2000 and is a Python, data science, and corporate training consultant. He is the author or coauthor of several books on Python. In the past, he has worked across the domains of search, build management and testing, business intelligence, and storage.

Textbooks for this course:

(Required) Matt Harrison, Effective Pandas: Patterns for Data Manipulation (Treading on Python) (ISBN 979-8772692936 )