Complete SQL course for Data Science - From Scratch

Veröffentlicht am: 20 Juni 2024
auf dem Kanal: Selva Prabhakaran (ML+)
580
31

Welcome to the ML+ course "SQL for Data Science". Let's learn all the essential concepts of SQL for Data Science from Scratch.

The Complete Data Science Course (Roadmap): https://edu.machinelearningplus.com/s...

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




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