Data Wrangling, Analysis and AB Testing with SQL

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课程主页: https://www.coursera.org/archive/data-wrangling-analysis-abtesting

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课程大纲

Data of Unknown Quality
Creating Clean Datasets
SQL Problem Solving
Case Study: AB Testing

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课程详情

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.

使用SQL进行数据整理,分析和AB测试:通过本课程,您可以将“ SQL for Data Science”中教授的SQL技能应用于四个日益复杂和可靠的数据科学查询案例研究。我们将学习如何将所有类型的时间戳转换为通用格式并执行日期/时间计算。我们将针对重复数据删除,运行质量检查,回填和处理空值,为数据科学查询和分析数据集中的数据选择并执行最佳JOIN。我们将学习如何使用窗口函数和用例语句执行条件逻辑来解决数据科学查询,从而按分段对数据进行分段和分析。我们还将描述如何将查询转换为计划的作业,以及如何将数据插入日期分区。最后,鉴于预测分析的需要,我们将使用在本课程中构建的工具和技能,从原始数据中设计一项功能。这些技能的实际应用将为您提供进行AB测试分析的框架。

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