Data Analysis Using Python

COM SCI X 418.106

This course introduces Pandas, one of the core Python data analysis packages, and uses it as the basis for performing various types of data analysis tasks. Essential data visualization techniques will also be covered. 

READ MORE ABOUT THIS COURSE
Fall
Remote Instruction
Starting at $995.00
As few as 10 weeks
4.0
3.3

What you can learn.

  • Leverage the Pandas package for data analysis
  • Learn data visualization techniques
  • Master data preparation, cleansing, format conversion, and presentation
  • Create statistical models using big datasets

About this course:

The easy to use nature of the Python language makes it an ideal candidate for performing data analysis. Related tasks such as data preparation, cleanup, data format conversion, and presentation are often part of the data analysis process. This course introduces Pandas, one of the core Python data analysis packages, and uses it as the basis for performing various types of data analysis tasks. The essential data visualization techniques will also be covered. 
Prerequisites
COM SCI X 418.104B Python Programming I or equivalent experience.

Fall 2020 Schedule

Available Format(s):

These courses have regular meeting times and are fully online, via remote instruction. Click “See Details” below for more information.

Future Offering (Opens August 03, 2020 12:00:00 AM)
-
Monday 6:00PM PDT - 9:30PM PST
Location: Online
Instructor: Shao-Ching Huang
374914
Fee:
$995.00
See Details
Notes
Enrollment limited. Enrollment deadline: October 4, 2020. Internet access required. Materials required.
Refund Deadline
No refunds after October 11, 2020
Schedule
Type
Date
Time
Location
Online
Mon Sep 28, 2020
6:00PM PDT - 9:30PM PST
Online
Online
Mon Oct 12, 2020
6:00PM PDT - 9:30PM PST
Online
Online
Mon Oct 26, 2020
6:00PM PDT - 9:30PM PST
Online
Online
Mon Nov 9, 2020
6:00PM PDT - 9:30PM PST
Online
Online
Mon Nov 23, 2020
6:00PM PDT - 9:30PM PST
Online

Contact Us

Our team members are here to help. Hours: Mon-Fri, 8am-5pm.

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