- Level: Intermediate
- Duration: 02h 38m
- Release date: 2021-07-20
- Author: Dan Sullivan
- Provider: LinkedIn
Intermediate SQL for Data Scientists
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.
- Introduction01m 11s
- The need for SQL in data science00m 31s
- What you should know00m 40s
- 1. Foundations of SQL for Data Science20m 32s
- Overview of data science operations07m 03s
- Data manipulation commands03m 52s
- Data definition commands04m 52s
- SQL standards02m 02s
- Installing PostgreSQL02m 43s
- 2. Basic Statistics with SQL31m 21s
- Loading data06m
- Basic aggregate functions05m 26s
- Statistical aggregate functions05m 53s
- Grouping and filtering data05m 39s
- Joining and filtering data07m 10s
- Challenge: Test an attribute for normal distribution00m 18s
- Solution: Test an attribute for normal distribution00m 55s
- 3. Data Munging with SQL35m 03s
- Reformat character data08m 24s
- Extract strings from character data06m 26s
- Filter with regular expressions07m 14s
- Reformat numeric data04m 11s
- Use SOUNDEX with misspelled text07m 50s
- Challenge: Prepare a data set for analysis00m 26s
- Solution: Prepare a data set for analysis00m 32s
- 4. Filtering and Aggregation33m 03s
- Use the HAVING clause to find subgroups06m 10s
- Subqueries for column values04m 33s
- Subqueries in FROM clauses03m 33s
- Subqueries in WHERE clauses02m 46s
- Use ROLLUP to create subtotals04m 56s
- Use CUBE to total across dimensions07m 35s
- Use Top-N queries to find top results02m 03s
- Challenge: Filter and aggregate a data set00m 26s
- Solution: Filter and aggregate a data set01m 01s
- 5. Window Functions and Ordered Data24m 07s
- Introduction to window functions04m 46s
- NTH_VALUE and NTILE06m 31s
- RANK, LEAD, and LAG04m 48s
- WIDTH_BUCKET and CUME_DIST07m 13s
- Challenge: Segment a data set using Window functions00m 23s
- Solution: Segment a data set using Window functions00m 26s
- 6. Common Table Expressions12m 44s
- Introduction to common table expressions (CTEs)00m 58s
- Multiple table common table expressions04m 16s
- Hierarchical tables02m 32s
- Recursive common table expressions03m 54s
- Challenge: Rewrite a complex query to use CTEs00m 35s
- Solution: Rewrite a complex query to use CTEs00m 29s
- Conclusion00m 48s
- Next steps00m 48s
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