Python for Data Analysis
Get a head start in your career by gaining essential data analysis skills. This online course in our Python for Data Analysis Professional Concentration is designed for professionals looking to develop relevant analysis skills in general or switch to a more technical career.
Python for Data Analysis will introduce basic data analysis applications of Python for those with little or no programming experience. Through remote lectures, group discussions and hands-on projects, you will learn how to ingest and clean data, plot basic graphs and fit regression-based models. Along with the basics of the Python language, you’ll get an introduction to various Python libraries, as well as learn how to import data and manipulate it efficiently using Pandas and NumPy, how to produce plots and data visualizations with matplotlib and how to run regression models using sci kit-learn. By the end of this course, you will be able to immediately apply your new skills to perform basic data analysis tasks in Python.
Learning Outcomes
- Read and explore data frames using various libraries including Pandas
- Analyze and make recommendations from a dataset
- Gain hands on experience testing a hypothesis using data
Skills You’ll Gain
- Basic data analysis in Python
- Experience with Pandas, NumPy and scikit-learn
Section Notes
This is an online course with class materials that can be accessed throughout the week. The course is structured to move from one week to the next.
Students will receive an email with login information to access the course 5 days before the course begins.
Students pursuing the full Professional Concentration in Python for Data Analysis must earn a grade of C or higher (not a C minus) in order for this course to count towards the requirements for the Professional Concentration. Courses applied towards the Professional Concentration in Python for Data Analysis must be completed within five years.
Refund Deadline: August 8, 2024. Refunds and/or enrollment transfers will not be approved after this date.
Enrollment Policies
Click here or visit https://cpe.ucdavis.edu/student-services/withdrawals-refunds-and-transfers to view complete enrollment policy information including details on withdrawals and transfers.
Refund Deadline: 8/5/2024. Refunds and/or enrollment transfers will not be approved after this date.
Prerequisites
Introduction to Python Programming (Course Number: 508127) or general knowledge of Python programming.