IS 537

Fall 2020 All Classes

All Classes

Theory & Practice of Data Cleaning

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Credit: 4 hours.

Data cleaning (also: cleansing) is the process of assessing and improving data quality for later analysis and use, and is a crucial part of data curation and analysis. This course identifies data quality issues throughout the data lifecycle, and reviews specific techniques and approaches for checking and improving data quality. Techniques are drawn primarily from the database community, using schema-level and instance-level information, and from different scientific communities, which are developing practical tools for data pre-processing and cleaning.

Same as CS 513. 4 graduate hours. No professional credit.

This course satisfies the General Education Criteria in Fall 2022 for:

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IS 537 class schedule data for fall 2020
	CRN	Type	Section	Time	Day	Location	Instructor	Section Details
	73169	Online	AO	3:30PM -5:30PM	R	n.a.	Cheng, J Ludaescher, B	Part of Term: 1 Date Range: 08/24/20-12/09/20 Degree Notes: ONL Info Science rate course. Section Title: Theory & Prac of Data Cleaning Section Info: This course meets with IS 537 AO1. Graduate student questions may be sent to ischool-advising@illinois.edu Restriction(s): Restricted to Graduate - Urbana-Champaign. Restricted to students in the Information Sciences department.
	73168	Online	AO1	3:30PM -5:30PM	R	n.a.	Cheng, J Ludaescher, B	Part of Term: 1 Date Range: 08/24/20-12/09/20 Degree Notes: ONL Info Science rate course. Section Title: Theory & Prac of Data Cleaning Section Info: This course meets with IS 537 AO. Graduate student questions may be sent to ischool-advising@illinois.edu Restriction(s): Restricted to Graduate - Urbana-Champaign. Restricted to students in the Information Sciences department.