[ FreeCourseWeb ] Linkedin - Intermediate SQL for Data Scientists

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[ FreeCourseWeb.com ] Linkedin - Intermediate SQL for Data Scientists
  • Get Bonus Downloads Here.url (0.2 KB)
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    • Bonus Resources.txt (0.3 KB)
      • Ex_Files_Intermediate_SQL_for_Data_Scientists Exercise Files CH02
      • 02_02.sql (0.5 KB)
      • 02_03.sql (1.0 KB)
      • 02_04.sql (0.5 KB)
      • 02_05.sql (0.8 KB)
      • exercise_data.sql (200.7 KB)
      CH03
      • 03_01.sql (1.1 KB)
      • 03_02.sql (0.6 KB)
      • 03_03.sql (1.4 KB)
      • 03_04.sql (0.5 KB)
      • 03_05.sql (0.7 KB)
      CH04
      • 04_01.sql (2.0 KB)
      • 04_02.sql (0.2 KB)
      • 04_03.sql (0.3 KB)
      • 04_04.sql (0.1 KB)
      • 04_05.sql (0.7 KB)
      • 04_06.sql (0.8 KB)
      • 04_07.sql (0.2 KB)
      • 04_09.sql (0.2 KB)
      CH05
      • 05_01.sql (0.2 KB)
      • 05_02.sql (0.4 KB)
      • 05_03.sql (0.9 KB)
      • 05_04.sql (0.3 KB)
      CH06
      • 06_02.sql (0.4 KB)
      • 06_03.sql (0.4 KB)
      • 06_04.sql (0.8 KB)
      • 06_05.sql (0.2 KB)
      [1] Introduction
      • [1] The need for SQL in data science.mp4 (2.9 MB)
      • [1] The need for SQL in data science.srt (1.0 KB)
      • [2] What you should know.mp4 (1.1 MB)
      • [2] What you should know.srt (1.3 KB)
      [2] 1. Foundations of SQL for Data Science
      • [1] Overview of data science operations.mp4 (18.4 MB)
      • [1] Overview of data science operations.srt (13.2 KB)
      • [2] Data manipulation commands.mp4 (6.2 MB)
      • [2] Data manipulation commands.srt (7.0 KB)
      • [3] Data definition commands.mp4 (8.1 MB)
      • [3] Data definition commands.srt (9.0 KB)
      • [4] SQL standards.mp4 (3.6 MB)
      • [4] SQL standards.srt (4.0 KB)
      • [5] Installing PostgreSQL.mp4 (7.4 MB)
      • [5] Installing PostgreSQL.srt (4.5 KB)
      [3] 2. Basic Statistics with SQL
      • [1] Loading data.mp4 (20.6 MB)
      • [1] Loading data.srt (10.9 KB)
      • [2] Basic aggregate functions.mp4 (16.2 MB)
      • [2] Basic aggregate functions.srt (9.9 KB)
      • [3] Statistical aggregate functions.mp4 (17.3 MB)
      • [3] Statistical aggregate functions.srt (9.2 KB)
      • [4] Grouping and filtering data.mp4 (15.8 MB)
      • [5] Joining and filtering data.mp4 (22.2 MB)
      • [5] Joining and filtering data.srt (11.9 KB)
      • [6] Challenge Test an attribute for normal distribution.mp4 (567.8 KB)
      • [7] Solution Test an attribute for normal distribution.mp4 (2.5 MB)
      • [7] Solution Test an attribute for normal distribution.srt (1.7 KB)
      [4] 3. Data Munging with SQL
      • [1] Reformat character data.mp4 (23.4 MB)
      • [1] Reformat character data.srt (13.2 KB)
      • [2] Extract strings from character data.mp4 (17.9 MB)
      • [2] Extract strings from character data.srt (9.8 KB)
      • [3] Filter with regular expressions.mp4 (19.4 MB)
      • [3] Filter with regular expressions.srt (11.1 KB)
      • [4] Reformat numeric data.mp4 (10.5 MB)
      • [4] Reformat numeric data.srt (6.6 KB)
      • [5] Use SOUNDEX with misspelled text.mp4 (20.0 MB)
      • [5] Use SOUNDEX with misspelled text.srt (11.0 KB)
      • [6] Challenge Prepare a data set for analysis.mp4 (868.7 KB)
      • [6] Challenge Prepare a data set for analysis.srt (0.6 KB)
      • [7] Solution Prepare a data set for analysis.mp4 (897.7 KB)
      • [7] Solution Prepare a data set for analysis.srt (0.9 KB)
      [5] 4. Filtering and Aggregation
      • [1] Use the HAVING clause to find subgroups.mp4 (16.3 MB)
      • [1] Use the HAVING clause to find subgroups.srt (9.4 KB)
      • [2] Subqueries for column values.mp4 (11.9 MB)
      • [2] Subqueries for column values.srt (6.6 KB)
      • [3] Subqueries in FROM clauses.mp4 (9.4 MB)
      • [3] Subqueries in FROM clauses.srt (5.3 KB)
      • [4] Subqueries in WHERE clauses.mp4 (7.3 MB)
      • [4] Subqueries in WHERE clauses.srt (3.9 KB)
      • [5] Use ROLLUP to create subtotals.mp4 (13.6 MB)
      • [5] Use ROLLUP to create subtotals.srt (7.8 KB)
      • [6] Use CUBE to total across dimensions.mp4 (23.3 MB)
      • [6] Use CUBE to total across dimensions.srt (12.0 KB)
      • [7] Use Top-N queries to find top results.mp4 (6.1 MB)
      • [7] Use Top-N queries to find top results.srt (3.0 KB)
      • [8] Challenge Filter and aggregate a data set.mp4 (845.7 KB)
      • [8] Challenge Filter and aggregate a data set.srt (0.7 KB)
      • [9] Solution Filter and aggregate a data set.mp4 (2.8 MB)
      • [9] Solution Filter and aggregate a data set.srt (1.8 KB)
      [6] 5. Window Functions and Ordered Data
      • [1] Introduction to window functions.mp4 (13.8 MB)
      • [1] Introduction to window functions.srt (7.9 KB)
      • [2] NTH_VALUE and NTILE.mp4 (17.8 MB)
      • [2] NTH_VALUE and NTILE.srt (10.4 KB)
      • [3] RANK, LEAD, and LAG.mp4 (14.4 MB)
      • [3] RANK, LEAD, and LAG.srt (7.4 KB)
      • [4] WIDTH_BUCKET and CUME_DIST.mp4 (22.2 MB)
      • [4] WIDTH_BUCKET and CUME_DIST.srt (11.9 KB)
      • [5] Challenge Segment a data set using Window functions.mp4 (720.3 KB)
      • [5] Challenge Segment a data set using Window functions.srt (0.5 KB)
      • [6] Solution Segment a data set using Window functions.mp4 (1.1 MB)
      • [6] Solution Segment a data set using Window functions.srt (0.6 KB)
      [7] 6. Common Table Expressions
      • [1] Introduction to common table expressions (CTEs).mp4 (1.7 MB)
      • [1] Introduction to common table expressions (CTEs).srt (1.6 KB)
      • [2] Multiple table common table expressions.mp4 (11.4 MB)
      • [2] Multiple table common table expressions.srt (5.

Description

Intermediate SQL for Data Scientists



MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 2h 38m | Size: 383.5 MB
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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[ FreeCourseWeb ] Linkedin - Intermediate SQL for Data Scientists

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429.9 MB
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[ FreeCourseWeb ] Linkedin - Intermediate SQL for Data Scientists

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