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Clean Your Data

In this course, you’ll explore three exploratory data analysis (EDA) practices: cleaning, joining, and validating. You'll discover the importance of these practices for data analysis, and you’ll use Python to clean, validate, and join data. By the end of this course, you will be able to: • Apply input validation skills to a dataset with Python • Explain the importance of input validation • Demonstrate how to transform categorical data into numerical data with Python • Explain the importance of categorical versus numerical data in a dataset • Explain the importance of recognizing outliers in a dataset • Demonstrate how to identify outliers in a dataset with Python • Understand when to contact stakeholders or engineers regarding missing values • Explain the importance of ethically considering missing values • Demonstrate how to identify missing data with Python

Status: Data Processing
Status: Data Integration
IntermediateCourse6 hours

Featured reviews

MM

Reviewed Nov 20, 2025

From the Python course, I learned the foundational skills of programming, such as writing code, using variables, loops, and functions, and understanding how to solve problems using Python.”

RA

Reviewed Feb 1, 2026

It's an amazing course with so much useful and practical material. It's ideal to start your Data science/Data Analysis journey with Python.

TH

Reviewed Dec 15, 2025

his course helped me understand the basics clearly and improved my practical skills. Well structured and easy to follow.

All reviews

Showing: 10 of 10

Mapula
5.0
Reviewed Nov 21, 2025
Raidel
5.0
Reviewed Feb 1, 2026
Tushar
5.0
Reviewed Dec 15, 2025
Sang
5.0
Reviewed Jul 11, 2026
Putra
5.0
Reviewed Jul 14, 2026
marwanto
5.0
Reviewed May 30, 2026
Pham
5.0
Reviewed Oct 28, 2025
Bryan
4.0
Reviewed May 29, 2026
Gustavo
3.0
Reviewed Apr 30, 2026
Deleted
3.0
Reviewed Mar 4, 2026