SQL for Data Science - Level I

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Section 1: Introduction to SQL

  1. Why you should learn SQL
  2. Resources for the "SQL for Data Science - Level 1"
  3. Types of SQL Servers
  4. Create new table from existing table
  5. Course Review

Section 2: Setting up Environments

  1. Setup Python Environment for SQL
  2. Import necessary libraries and create sample data
  3. Create DB and Run SQL in Jupyter Environment
  4. Data Wrangling iin SQL vs Python
  5. Setup MySQL Workbench

Section 3: Creating and Deleting Data

  1. Create a Table Manually in DB
  2. Exercise Create orders tables from raw data
  3. Create new table from existing table
  4. Show Table from existing database
  5. SQL DELETE - Delete rows in an existing dataset using where condition
  6. Delete a Table

Section 4: Selecting Data and Update Tables

  1. SQL Update Update rows-columns in an existing dataset
  2. Exercise 2: Updating Table
  3. SQL SELECT - Select Data required variables from a Dataset
  4. SQL Comments
  5. Limit the number of rows returned from a query

Section 5: Filtering Data

  1. Select Distinct Identify and delete duplicates in a dataset
  2. SQL Where Filtering rows
  3. SQL order by Sort the data in ascending or descending order
  4. SQL Having Filter rows after aggregating

Section 6: Merging Dataset

  1. Joining Datasets
  2. Exercise 4: Joining Exercise
  3. SQL DateTime Operations
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