Data Preparation, Modeling and Visualization with Python

Online

Gain the tools you need to succeed in a data-oriented career. This online course is the fifth part in our Professional Concentration in Python for Data Science, Web and Core Programming and is designed for professionals looking to develop relevant software skills in general or switch to a more technical career.

Data Preparation, Modeling and Visualization with Python will teach you how to create business value by effectively importing, preparing, modeling and visualizing data using Python. You will learn how to implement various models like linear regression, logistic regression and decision trees using both supervised and unsupervised modeling techniques. This course will primarily cover the Python packages pandas and scikit-learn, which will provide a useful toolkit for professionals in machine learning, data science, data mining or web data fields.

Learning Outcomes

  • Practice cleaning and visualizing data
  • Learn how to fit predictive models using Python
  • Assess efficient ways to explore data
  • Understand how to deal with common data preparation tasks

Skills You’ll Gain

  • Data preparation and modeling
  • Experience with pandas and scikit-learn
Academic Units
2
Section Number
223PYT305
Instruction Method
Online class

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 on the first day of class.

Students pursuing the full Professional Concentration in Python for Data Science, Web and Core Programming 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 Science, Web and Core Programming must be completed within five years.

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.

Prerequisites

Introduction to Python Programming (Course Number: 508127) or Python for Data Analysis (Course Number: 508130)

 

Technical Requirements

To ensure your success in this online course, please review our technical requirements page.

Discounts

Early Enroll Discount

Enroll 14 days before the course start date to save $50 on the course fee.

Info Session Discount

Attendees of UC Davis Continuing and Professional Education Information Sessions may be eligible for $100 discount on a class by entering the Coupon Code provided at the Information Session.  Contact UC Davis Continuing and Professional Education Student Services office, at (800) 752-0881, if you have questions about this discount.