Advanced Data Wrangling
Offered By: Udacity
Course Description
Overview
Data wrangling is a set of processes for turning raw and messy data into a clean format to answer interesting questions from the data. In this course, you will learn the three phases of data wrangling: gathering, assessing, and cleaning data.
Syllabus
- Introduction to Data Wrangling
- You will learn what data wrangling is and why it matters. And you will see a real-world example of data wrangling and some common misconceptions about data wrangling.
- Gathering Data
- You will learn to implement data gathering methods to obtain and extract data from various sources and in several popular data formats.
- Assessing Data
- You will learn to identify different data quality and structural issues and apply visual and programmatic assessments to catch them.
- Cleaning Data
- You will learn to remediate the issues you identified in the assessment stage and test that your data cleaning is successful.
- Real World Data Wrangling with Python
- You will apply the skills you acquired in the course by gathering, assessing, and cleaning multiple real-world datasets of your choice.
Taught by
cd1827 Ria Cheruvu
Related Courses
Artificial Intelligence for RoboticsStanford University via Udacity Intro to Computer Science
University of Virginia via Udacity Design of Computer Programs
Stanford University via Udacity Web Development
Udacity Programming Languages
University of Virginia via Udacity