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Data Wrangling, Analysis and AB Testing with SQL

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.

Created by University of California, Davis


What you’ll learn

In this educational resource you can improve the compentencies demanded by employers these days. The most in demand technique within the educational opportunity that is frequently included by organizations is Data Analysis. The most relevant tool is SQL. You will also hear about Problem Solving Skills, a trait often included in job postings.

Who will benefit?

Mapping the description from this learning resource with nearly 10,000 data-related job maps, we determine that those in or pursuing Data Scientist roles would benefit the most.