Learn how to execute core SQL commands to define, select, manipulate, control access, aggregate, and join data and data tables. Understand when and how to use subqueries, several window functions, and partitions to complete complex tasks. Clean data, optimize SQL queries and write select advanced JOINs to enhance analysis performance.
In this section, you will gain knowledge about SQL basics for working with a single table. You will learn the key commands to filter a table in many different ways.
In this lesson, you will learn how to combine data from multiple tables together.
In this lesson, you will learn how to aggregate data using SQL functions like SUM, AVG, and COUNT. Additionally, CASE, HAVING, and DATE functions provide you an incredible problem solving toolkit.
In this lesson, you will be learning to answer much more complex business questions using nested querying methods - also known as subqueries.
Cleaning data is an important part of the data analysis process. You will be learning how to perform data cleaning using SQL in this lesson.
Compare one row to another without doing any joins using one of the most powerful concepts in SQL data analysis: window functions.
Learn advanced joins and how to make queries that run quickly across giant datasets. Most of the examples in the lesson involve edge cases, some of which come up in interviews.
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MIT 18.650 Statistics for Applications, Fall 2016 View the complete course: http://ocw.mit.edu/18-650F16 Instructor: Philippe Rigollet This course offers an in-depth the theoretical foundations for statistical methods that are useful in many applications. The goal is to understand the role of mathe…
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Led by Andrew Ng, this course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (cluster…
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