Data Analytics track

Data Cleaning

Missing values, duplicates, outliers, type coercion and cleaning pipelines.

8 concepts5 labs1 challenges
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Concepts

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1

Data Quality Dimensions

Concept · Hands-on lab included

2

Handling Missing Data

Concept · Hands-on lab included

3

Detecting and Handling Duplicates

Concept · Hands-on lab included

4

Standardizing Text and Strings

Concept · Hands-on lab included

5

Type Coercion and Parsing

Concept · Hands-on lab included

6

Outlier Detection and Treatment

Concept · Hands-on lab included

7

Integrity and Foreign Keys

Concept · Hands-on lab included

8

Building a Cleaning Pipeline

Concept · Hands-on lab included

Practice

Hands-on labs

Apply what you've learned in guided, production-style environments.

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