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LinkedIn Learning

SQL for Exploratory Data Analysis Essential Training

via LinkedIn Learning

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Overview

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Learn how to use SQL to understand the characteristics of data sets destined for data science and machine learning.

Syllabus

Introduction
  • Welcome
  • What you should know
  • Tour of CoderPad
1. Introduction to Exploratory Data Analysis
  • Why explore data?
  • Exploring data with statistics
  • Testing hypothesis with statistics
2. Data Quality Checks
  • Why check data?
  • Types of quality checks
  • Imputing missing values
  • Identifying business logic checks
3. Calculating Quartiles
  • Why learn about the distribution of data?
  • Minimum, maximum, and median values
  • Ordering and counting
  • Calculating quartiles
  • Introduction to box plots
4. Histograms
  • Introduction to histograms
  • Partitioning data
  • Calculating histograms
  • Simple histogram visualization
5. Checking Correlation between Attributes
  • Introduction to correlation
  • Calculating correlation with SQL
  • Challenge: Calculating correlation with SQL
  • Solution: Calculating correlation with SQL
Conclusion
  • Next steps

Taught by

Dan Sullivan

Reviews

4.6 rating at LinkedIn Learning based on 533 ratings

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