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Introduction to Data Cleaning with Python

Data Science & Analytics

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5 courses

83 practices

6 hours

Master data cleaning with Python—handle missing values, fix messy columns, and prep data for machine learning. Learn powerful Pandas tricks, automate your workflows, and clean text like a pro.

4.62

541 learners

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Verified skills you'll gain

ADVANCED

Data Cleaning and Preprocessing

DEVELOPING

Exploratory Data Analysis

Tools you'll use

Pandas

Python

Course 1

Introduction to Data Cleaning with Python

5 lessons

19 practices

This course introduces fundamental concepts of data cleaning using Python, covering essential libraries, handling missing values, detecting and removing duplicates, dealing with outliers, and normalizing data for analysis.

Course 2

Cleaning and Transforming Data with Pandas

5 lessons

19 practices

This course explores advanced Pandas functionalities for transforming data, handling categorical and text data, processing date-time values, and performing feature engineering for better analysis.

Course 3

Data Cleaning and Validation for Machine Learning with Python

4 lessons

15 practices

This course ensures data integrity, feature selection, anomaly detection, and validation for ML models. The goal is to remove noisy, inconsistent, or biased data before training.

Course 4

Automating Data Cleaning with Python

4 lessons

15 practices

This course focuses on automating the data cleaning process using Python. It covers pipeline creation, automation with functions, handling large datasets efficiently, and logging and debugging.

Course 5

Advanced Data Cleaning: Handling Text Data with Python

4 lessons

15 practices

This course extends data cleaning techniques to handle text-based data in tabular datasets. It covers cleaning and processing text columns, dealing with mixed data types, extracting meaningful features from text, and preparing text data for machine learning.

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