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.
Offert par
Spécialisation Learn SQL Basics for Data ScienceUniversité de Californie à DavisÀ propos de ce cours
Some statistics is recommended and at least 2-years business experience.
Ce que vous allez apprendre
Validate and clean a dataset
Assess and create datasets to answer your questions
Solve problems using SQL
Build a simple testing framework to touch on AB Testing
Compétences que vous acquerrez
Some statistics is recommended and at least 2-years business experience.
Offert par
Université de Californie à Davis
UC Davis, one of the nation’s top-ranked research universities, is a global leader in agriculture, veterinary medicine, sustainability, environmental and biological sciences, and technology. With four colleges and six professional schools, UC Davis and its students and alumni are known for their academic excellence, meaningful public service and profound international impact.
Programme du cours : ce que vous apprendrez dans ce cours
Data of Unknown Quality
In this module, you will be able to create trustworthy analysis from a new set of data. You will be able to coalesce some nulls and identify unreliable data and discover reasons why data might be missing. You will also be able to answer ambiguous questions by defining new metrics.
Creating Clean Datasets
In this module, you will be able to name the main the categories of data types. You will be able to explain how the unfiltered data can be manipulated into a table where you can conduct data analysis. You will be able to discuss why a data warehouse is separate from a production database, and you will be able to use the tools you learned to create your own trustworthy tables.
SQL Problem Solving
In this module, you will be able to map out your joins and be able to highlight the level of detail needed for different kinds of questions. You will be able to practice answering data questions, which should help you feel ready to get asked a whole slough of questions, vague questions, ambiguous questions, or even poorly worded questions. Finally, you will develop a strategy for answering all those questions using data.
Case Study: AB Testing
In this module, you will be able to use your SQL skills to set up a basic AB testing system. You will be able to apply hypothesis testing to prove or disprove a hypothesis about how user behavior changed. You will be able to test and interpret the results using a metric or metrics that are tied directly to some business metrics. You will be able to test your SQL skills and give you the base experience you need to learn anything more complicated in terms of AB testing in the future.
Avis
Meilleurs avis pour DATA WRANGLING, ANALYSIS AND AB TESTING WITH SQL
A good course for learning and apply sql to conduct analysis on ab testing results. Would be better if the instructor could provide more info about how to design and apply AB Testing on the customers
The instructor is very smart and her syllabus is very easy to follow. The real life examples are great and helps put ideas in perspective! I would definitely recommend this course and already have!
It is pretty useful course to understand how to prepare data for AB Testing in real database environment. you should know SQL intermediate leve before starting this course.
A very thorough overview of SQL and how to best structure data tables and metrics for AB testing. I appreciate the high quality content of the UC Davis courses!
À propos du Spécialisation Learn SQL Basics for Data Science
This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency. Through four progressively more difficult SQL projects with data science applications, you will cover topics such as SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, and more. These topics will prepare you to apply SQL creatively to analyze and explore data; demonstrate efficiency in writing queries; create data analysis datasets; conduct feature engineering, use SQL with other data analysis and machine learning toolsets; and use SQL with unstructured data sets.
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