Intermediate SQL for Data Scientists

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Dan Sullivan

2:38:49

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[1] Introduction

[1] The need for SQL in data science.mp4

00:31

[2] What you should know.mp4

00:40

[2] 1. Foundations of SQL for Data Science

[1] Overview of data science operations.mp4

07:03

[2] Data manipulation commands.mp4

03:52

[3] Data definition commands.mp4

04:52

[4] SQL standards.mp4

02:02

[5] Installing PostgreSQL.mp4

02:43

[3] 2. Basic Statistics with SQL

[1] Loading data.mp4

06:00

[2] Basic aggregate functions.mp4

05:26

[3] Statistical aggregate functions.mp4

05:53

[4] Grouping and filtering data.mp4

05:39

[5] Joining and filtering data.mp4

07:10

[6] Challenge Test an attribute for normal distribution.mp4

00:18

[7] Solution Test an attribute for normal distribution.mp4

00:55

[4] 3. Data Munging with SQL

[1] Reformat character data.mp4

08:24

[2] Extract strings from character data.mp4

06:26

[3] Filter with regular expressions.mp4

07:14

[4] Reformat numeric data.mp4

04:11

[5] Use SOUNDEX with misspelled text.mp4

07:50

[6] Challenge Prepare a data set for analysis.mp4

00:26

[7] Solution Prepare a data set for analysis.mp4

00:32

[5] 4. Filtering and Aggregation

[1] Use the HAVING clause to find subgroups.mp4

06:10

[2] Subqueries for column values.mp4

04:33

[3] Subqueries in FROM clauses.mp4

03:33

[4] Subqueries in WHERE clauses.mp4

02:46

[5] Use ROLLUP to create subtotals.mp4

04:56

[6] Use CUBE to total across dimensions.mp4

07:35

[7] Use Top-N queries to find top results.mp4

02:03

[8] Challenge Filter and aggregate a data set.mp4

00:26

[9] Solution Filter and aggregate a data set.mp4

01:01

[6] 5. Window Functions and Ordered Data

[1] Introduction to window functions.mp4

04:46

[2] NTH VALUE and NTILE.mp4

06:31

[3] RANK, LEAD, and LAG.mp4

04:48

[4] WIDTH BUCKET and CUME DIST.mp4

07:13

[5] Challenge Segment a data set using Window functions.mp4

00:23

[6] Solution Segment a data set using Window functions.mp4

00:26

[7] 6. Common Table Expressions

[1] Introduction to common table expressions (CTEs).mp4

00:58

[2] Multiple table common table expressions.mp4

04:16

[3] Hierarchical tables.mp4

02:32

[4] Recursive common table expressions.mp4

03:54

[5] Challenge Rewrite a complex query to use CTEs.mp4

00:35

[6] Solution Rewrite a complex query to use CTEs.mp4

00:29

[8] Conclusion

[1] Next steps.mp4

00:48

Description

There is an increasing need for data scientists and analysts to understand relational data stores. Organizations have long used SQL databases to store transactional data as well as business intelligence related data. This course was designed for data scientists who need to work with SQL databases. Specifically, it was designed to help these professionals learn how to perform common data science tasks, including exploration and extraction of data within relational databases.

Instructor Dan Sullivan kicks off the course with a brief overview of SQL data manipulation and data definition commands. He then focuses on how to use SQL queries to prepare data for analysis; leverage statistical functions to better understand that data; and work with aggregates, window operations, and more.

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Data Science

Dan Sullivan

Instructor's Courses

Cloud and data architect with extensive experience in data architecture, data science, machine learning, stream processing, and cloud architecture. Capable of starting with vague initiatives and formulating precise objectives, strategies, and implementation plans. Regularly works with C-level and VP executives while also mentoring and coaching software engineers. Adapts well to unforeseen challenges. He is the author of the official Google Cloud study guides for the Professional Architect, Professional Data Engineer, and Associate Cloud Engineer.

Linkedin Learning

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.