Data Wrangling, Analysis and AB Testing with SQL
Master advanced SQL techniques for data cleaning, analysis, and AB testing through real-world case studies and hands-on practice.
Master advanced SQL techniques for data cleaning, analysis, and AB testing through real-world case studies and hands-on practice.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Learn SQL Basics for Data Science Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
3.3
(956 ratings)
69,624 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 3 more
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What you'll learn
Clean and validate complex datasets using SQL
Create and analyze AB tests with statistical rigor
Build efficient data processing pipelines
Develop metrics for business analysis
Implement advanced SQL problem-solving techniques
Skills you'll gain
This course includes:
4.5 Hours PreRecorded video
9 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course focuses on applying SQL skills to real-world data science scenarios. Students learn to clean and validate datasets, create analysis-ready tables, and implement AB testing frameworks. The curriculum covers advanced topics including data type manipulation, windowing functions, conditional logic, and feature engineering. Through case studies and hands-on exercises, participants develop practical skills in data wrangling and statistical analysis.
Data of Unknown Quality
Module 1 · 5 Hours to complete
Creating Clean Datasets
Module 2 · 2 Hours to complete
SQL Problem Solving
Module 3 · 3 Hours to complete
Case Study: AB Testing
Module 4 · 3 Hours to complete
Fee Structure
Instructor
Accomplished Senior Data Scientist at OpenSpace.ai
Katrina Glaeser Poole is a Senior Data Scientist at OpenSpace.ai, where she leverages her expertise in data science to drive innovation in the construction industry. She earned her Master’s degree in Mathematics from the University of California, Davis, where she developed a passion for teaching and was nominated for the Outstanding Graduate Teaching Award for her work on an online linear algebra course. Kat began her career at Yammer, where she played a pivotal role in introducing A/B testing principles to Microsoft's Office team. She later joined Pandora Media, contributing to a small team focused on enhancing artist-fan engagement through data-driven insights. Prior to her current role at OpenSpace.ai, she served as the Lead Data Scientist at Marco Polo, a video communication app designed to help users maintain connections despite busy lives. Outside of her professional endeavors, Kat enjoys trail running with her dog, sending snail mail, and bike touring, reflecting her active lifestyle and commitment to community engagement.
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3.3 course rating
956 ratings
Frequently asked questions
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