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Data Wrangling, Analysis and AB Testing with SQL

This course is a part of Learn SQL Basics for Data Science, a 4-course Specialization series from Coursera.

This course allows you to apply the SQL skills taught in “SQL for Data Science” to four increasingly complex and authentic data science inquiry case studies. We'll learn how to convert timestamps of all types to common formats and perform date/time calculations. We'll select and perform the optimal JOIN for a data science inquiry and clean data within an analysis dataset by deduping, running quality checks, backfilling, and handling nulls. We'll learn how to segment and analyze data per segment using windowing functions and use case statements to execute conditional logic to address a data science inquiry. We'll also describe how to convert a query into a scheduled job and how to insert data into a date partition. Finally, given a predictive analysis need, we'll engineer a feature from raw data using the tools and skills we've built over the course. The real-world application of these skills will give you the framework for performing the analysis of an AB test.

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University of California, Davis

Rating Not enough ratings
Length 5 weeks
Effort 4 weeks of study, 2-5 hours/week
Starts Jul 6 (5 weeks ago)
Cost $49
From University of California, Davis via Coursera
Instructor Katrina Glaeser
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Programming
Tags Data Science Data Analysis Machine Learning

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Coursera

&

University of California, Davis

Rating Not enough ratings
Length 5 weeks
Effort 4 weeks of study, 2-5 hours/week
Starts Jul 6 (5 weeks ago)
Cost $49
From University of California, Davis via Coursera
Instructor Katrina Glaeser
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Programming
Tags Data Science Data Analysis Machine Learning

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