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02_02.sql
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SQL
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512 B
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02_03.sql
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SQL
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1 KB
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02_04.sql
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SQL
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512 B
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02_05.sql
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SQL
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819.2 B
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03_01.sql
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SQL
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1.1 KB
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03_02.sql
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SQL
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614.4 B
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03_03.sql
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SQL
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1.4 KB
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03_04.sql
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SQL
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512 B
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03_05.sql
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SQL
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716.8 B
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04_01.sql
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SQL
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2 KB
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04_02.sql
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SQL
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204.8 B
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04_03.sql
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SQL
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307.2 B
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04_04.sql
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SQL
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102.4 B
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04_05.sql
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SQL
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716.8 B
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04_06.sql
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SQL
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819.2 B
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04_07.sql
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SQL
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204.8 B
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04_09.sql
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SQL
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204.8 B
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05_01.sql
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SQL
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204.8 B
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05_02.sql
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SQL
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409.6 B
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05_03.sql
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SQL
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921.6 B
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05_04.sql
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SQL
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307.2 B
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06_02.sql
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SQL
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409.6 B
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06_03.sql
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SQL
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409.6 B
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06_04.sql
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SQL
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819.2 B
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06_05.sql
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SQL
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204.8 B
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Bonus Resources.txt
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TXT
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307.2 B
|
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Get Bonus Downloads Here.url
|
URL
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204.8 B
|
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[1] Introduction to common table expressions (CTEs).mp4
|
MP4
|
1.7 MB
|
|
|
[1] Introduction to common table expressions (CTEs).srt
|
SRT
|
1.6 KB
|
|
|
[1] Introduction to window functions.mp4
|
MP4
|
13.8 MB
|
|
|
[1] Introduction to window functions.srt
|
SRT
|
7.9 KB
|
|
|
[1] Loading data.mp4
|
MP4
|
20.6 MB
|
|
|
[1] Loading data.srt
|
SRT
|
10.9 KB
|
|
|
[1] Next steps.mp4
|
MP4
|
1.5 MB
|
|
|
[1] Next steps.srt
|
SRT
|
1.6 KB
|
|
|
[1] Overview of data science operations.mp4
|
MP4
|
18.4 MB
|
|
|
[1] Overview of data science operations.srt
|
SRT
|
13.2 KB
|
|
|
[1] Reformat character data.mp4
|
MP4
|
23.4 MB
|
|
|
[1] Reformat character data.srt
|
SRT
|
13.2 KB
|
|
|
[1] The need for SQL in data science.mp4
|
MP4
|
2.9 MB
|
|
|
[1] The need for SQL in data science.srt
|
SRT
|
1 KB
|
|
|
[1] Use the HAVING clause to find subgroups.mp4
|
MP4
|
16.3 MB
|
|
|
[1] Use the HAVING clause to find subgroups.srt
|
SRT
|
9.4 KB
|
|
|
[2] Basic aggregate functions.mp4
|
MP4
|
16.2 MB
|
|
|
[2] Basic aggregate functions.srt
|
SRT
|
9.9 KB
|
|
|
[2] Data manipulation commands.mp4
|
MP4
|
6.2 MB
|
|
|
[2] Data manipulation commands.srt
|
SRT
|
7 KB
|
|
|
[2] Extract strings from character data.mp4
|
MP4
|
17.9 MB
|
|
|
[2] Extract strings from character data.srt
|
SRT
|
9.8 KB
|
|
|
[2] Multiple table common table expressions.mp4
|
MP4
|
11.4 MB
|
|
|
[2] Multiple table common table expressions.srt
|
SRT
|
5.5 KB
|
|
|
[2] NTH_VALUE and NTILE.mp4
|
MP4
|
17.8 MB
|
|
|
[2] NTH_VALUE and NTILE.srt
|
SRT
|
10.4 KB
|
|
|
[2] Subqueries for column values.mp4
|
MP4
|
11.9 MB
|
|
|
[2] Subqueries for column values.srt
|
SRT
|
6.6 KB
|
|
|
[2] What you should know.mp4
|
MP4
|
1.1 MB
|
|
|
[2] What you should know.srt
|
SRT
|
1.3 KB
|
|
|
[3] Data definition commands.mp4
|
MP4
|
8.1 MB
|
|
|
[3] Data definition commands.srt
|
SRT
|
9 KB
|
|
|
[3] Filter with regular expressions.mp4
|
MP4
|
19.4 MB
|
|
|
[3] Filter with regular expressions.srt
|
SRT
|
11.1 KB
|
|
|
[3] Hierarchical tables.mp4
|
MP4
|
5.5 MB
|
|
|
[3] Hierarchical tables.srt
|
SRT
|
4.2 KB
|
|
|
[3] RANK, LEAD, and LAG.mp4
|
MP4
|
14.4 MB
|
|
|
[3] RANK, LEAD, and LAG.srt
|
SRT
|
7.4 KB
|
|
|
[3] Statistical aggregate functions.mp4
|
MP4
|
17.3 MB
|
|
|
[3] Statistical aggregate functions.srt
|
SRT
|
9.2 KB
|
|
|
[3] Subqueries in FROM clauses.mp4
|
MP4
|
9.4 MB
|
|
|
[3] Subqueries in FROM clauses.srt
|
SRT
|
5.3 KB
|
|
|
[4] Grouping and filtering data.mp4
|
MP4
|
15.8 MB
|
|
|
[4] Recursive common table expressions.mp4
|
MP4
|
9.4 MB
|
|
|
[4] Recursive common table expressions.srt
|
SRT
|
5.1 KB
|
|
|
[4] Reformat numeric data.mp4
|
MP4
|
10.5 MB
|
|
|
[4] Reformat numeric data.srt
|
SRT
|
6.6 KB
|
|
|
[4] SQL standards.mp4
|
MP4
|
3.6 MB
|
|
|
[4] SQL standards.srt
|
SRT
|
4 KB
|
|
|
[4] Subqueries in WHERE clauses.mp4
|
MP4
|
7.3 MB
|
|
|
[4] Subqueries in WHERE clauses.srt
|
SRT
|
3.9 KB
|
|
|
[4] WIDTH_BUCKET and CUME_DIST.mp4
|
MP4
|
22.2 MB
|
|
|
[4] WIDTH_BUCKET and CUME_DIST.srt
|
SRT
|
11.9 KB
|
|
|
[5] Challenge Rewrite a complex query to use CTEs.mp4
|
MP4
|
1.3 MB
|
|
|
[5] Challenge Rewrite a complex query to use CTEs.srt
|
SRT
|
921.6 B
|
|
|
[5] Challenge Segment a data set using Window functions.mp4
|
MP4
|
720.3 KB
|
|
|
[5] Challenge Segment a data set using Window functions.srt
|
SRT
|
512 B
|
|
|
[5] Installing PostgreSQL.mp4
|
MP4
|
7.4 MB
|
|
|
[5] Installing PostgreSQL.srt
|
SRT
|
4.5 KB
|
|
|
[5] Joining and filtering data.mp4
|
MP4
|
22.2 MB
|
|
|
[5] Joining and filtering data.srt
|
SRT
|
11.9 KB
|
|
|
[5] Use ROLLUP to create subtotals.mp4
|
MP4
|
13.6 MB
|
|
|
[5] Use ROLLUP to create subtotals.srt
|
SRT
|
7.8 KB
|
|
|
[5] Use SOUNDEX with misspelled text.mp4
|
MP4
|
20 MB
|
|
|
[5] Use SOUNDEX with misspelled text.srt
|
SRT
|
11 KB
|
|
|
[6] Challenge Prepare a data set for analysis.mp4
|
MP4
|
868.7 KB
|
|
|
[6] Challenge Prepare a data set for analysis.srt
|
SRT
|
614.4 B
|
|
|
[6] Challenge Test an attribute for normal distribution.mp4
|
MP4
|
567.8 KB
|
|
|
[6] Solution Rewrite a complex query to use CTEs.mp4
|
MP4
|
1.3 MB
|
|
|
[6] Solution Rewrite a complex query to use CTEs.srt
|
SRT
|
716.8 B
|
|
|
[6] Solution Segment a data set using Window functions.mp4
|
MP4
|
1.1 MB
|
|
|
[6] Solution Segment a data set using Window functions.srt
|
SRT
|
614.4 B
|
|
|
[6] Use CUBE to total across dimensions.mp4
|
MP4
|
23.3 MB
|
|
|
[6] Use CUBE to total across dimensions.srt
|
SRT
|
12 KB
|
|
|
[7] Solution Prepare a data set for analysis.mp4
|
MP4
|
897.7 KB
|
|
|
[7] Solution Prepare a data set for analysis.srt
|
SRT
|
921.6 B
|
|
|
[7] Solution Test an attribute for normal distribution.mp4
|
MP4
|
2.5 MB
|
|
|
[7] Solution Test an attribute for normal distribution.srt
|
SRT
|
1.7 KB
|
|
|
[7] Use Top-N queries to find top results.mp4
|
MP4
|
6.1 MB
|
|
|
[7] Use Top-N queries to find top results.srt
|
SRT
|
3 KB
|
|
|
[8] Challenge Filter and aggregate a data set.mp4
|
MP4
|
845.7 KB
|
|
|
[8] Challenge Filter and aggregate a data set.srt
|
SRT
|
716.8 B
|
|
|
[9] Solution Filter and aggregate a data set.mp4
|
MP4
|
2.8 MB
|
|
|
[9] Solution Filter and aggregate a data set.srt
|
SRT
|
1.8 KB
|
|
|
exercise_data.sql
|
SQL
|
200.7 KB
|
![[ FreeCourseWeb ] Linkedin - Intermediate SQL for Data Scientists](/static/img/no-torrent-image.png "[ FreeCourseWeb ] Linkedin - Intermediate SQL for Data Scientists")
