Complete SQL course for Data Science - From Scratch

Welcome to the "SQL for Data Science" course. Let's learn all the essential concepts of SQL for Data Science from Scratch. Chapters: 00:00 Why you should learn SQL? 06:48 Types of Server 11:27 Setup Python Environment for SQL 18:38 Import necessary libraries and create sample data 21:16 Create DB and Run SQL in Jupyter Environment 35:13 Data Wrangling iin SQL vs Python 45:22 Setup MySQL Workbench 1:02:23 Create a table manually in DB 1:10:41 Exercise: Create orders table from raw data 1:11:59 Create new table from existing table 1:14:09 Show table from existing database 1:17:27 Insert into Select: Copy data from one table to another 1:19:22 SQL DELETE - Delete rows in an existing dataset using where condition 1:22:19 Delete a Table 1:22:53 SQL Update: Update rows-columns in an existing dataset 1:23:44 Exercise 2: Updating Table 1:32:40 SQL SELECT - Select Data required variables from a Dataset 1:34:31 SQL Comments 1:35:07 Limit the number of rows returned from a query 1:36:24 Select Distinct Identify and delete duplicates in a dataset 1:38:27 SQL Where Filtering rows 1:39:28 Exercise 3: Filtering Data 1:40:27 SQL order by Sort the data in ascending or descending order 1:42:35 SQL Having Filter rows after aggregating 1:44:18 Joining Datasets 1:50:00 Exercise 4: Joining Exercise 1:50:43 SQL DateTime Operations 1:53:51 SQL Null values 2:00:20 Self Assessment test - Instructions 2:12:18 Self Assessment test - Question 2:13:19 Self Assessment test - Solution 2:21:10 Logical Operators SQL And, Or, Not 2:24:24 SQL mini and max 2:27:06 SQL, count, avg, Sum and group by Index 2:29:08 SQL Like and Wildcards 2:33:44 SQL IN and Between 2:35:18 SQL Exists 2:48:12 SQL Aliases 2:48:57 SQL Case statements 2:50:29 SQL Operators 2:51:20 Exercise Set 2 2:57:07 Concatenation 2:58:22 Hard Questions 3:11:25 Length or Len 3:11:58 Lower and Upper 3:12:24 Trimming Text 3:13:45 Replace Occurrence 3:13:56 Exercise Set 3 3:17:49 Sub Queries 3:31:38 Sub Queries – Tougher example 1 3:48:01 Sub Queries – Tougher example 2 If you enjoyed this video, throw in a like and subscribe for future videos! Thanks for watching! #statisticsfordatascience #machinelearningplus #python #machinelearning #datascience #artificialintelligence