Data Cleaning
Offered By: Kaggle
Course Description
Overview
Master efficient workflows for cleaning real-world, messy data.
- Drop missing values, or fill them in with an automated workflow.
- Transform numeric variables to have helpful properties.
- Help Python recognize dates as composed of day, month, and year.
- Avoid UnicoodeDecodeErrors when loading CSV files.
- Efficiently fix typos in your data.
Syllabus
- Handling Missing Values
- Scaling and Normalization
- Parsing Dates
- Character Encodings
- Inconsistent Data Entry
Taught by
Rachael Tatman
Related Courses
Data Base Management SystemIndian Institute of Technology, Kharagpur via Swayam Healthcare Data Models
University of California, Davis via Coursera Image Data Augmentation with Keras
Coursera Project Network via Coursera Compare time series predictions of COVID-19 deaths
Coursera Project Network via Coursera Practicing Machine Learning Interview Questions in R
DataCamp