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Learn Data Cleaning with Python
Rating: 4.0 out of 5(337 ratings)
11,780 students

Learn Data Cleaning with Python

Perform Data Cleaning Techniques with the Python Programming Language. Practice and Solution Notebooks included.
Last updated 3/2020
English

What you'll learn

  • I can standardize a dataset by fixing inconsistent column names.
  • I can perform data type conversion to fix inaccurate data.
  • I can find and fix syntax errors in a dataset.
  • I can find and fix typos in a dataset.
  • I can deal with irrelevant data in a dataset.
  • I can remove any duplicate records in a dataset.
  • I can find and deal with missing data in a dataset.
  • I can find and deal with outliers in a dataset.

Course content

7 sections7 lectures50m total length
  • Introduction3:11

Requirements

  • You will need to have basic python programming proficiency.
  • You will need a modern browser i.e. Google Chrome or Mozilla Firefox.

Description

By the end of this course, you will be able to:

  • I can standardize a dataset by fixing inconsistent column names.

  • I can perform data type conversion to fix inaccurate data.

  • I can find and fix syntax errors in a dataset.

  • I can find and fix typos in a dataset.

  • I can deal with irrelevant data in a dataset.

  • I can remove any duplicate records in a dataset.

  • I can find and deal with missing data in a dataset.

  • I can find and deal with outliers in a dataset.


Who this course is for:

  • This course is designed for professionals with an interest in getting hands-on experience with the respective data science techniques and tools.