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Databases and SQL for Data Science with Python

📄 Summary

The purpose of this course is to introduce relational database concepts and to learn and apply foundational knowledge of the SQL language. It is also intended to provide a foundation to performing SQL access in a data science environment.

📑 Main Topics

• Getting Started with SQL

  • Introduction to Databases

  • SELECT Statements

  • COUNT, DISTINCT, LIMIT Statements

  • INSERT Statements

  • UPDATE and DELETE Statements

• Introduction to Relational Databases and Tables

  • Relational Database Concepts

  • Types of SQL statements (DDL vs. DML)

  • CREATE TABLE Statement

  • ALTER, DROP, and Truncate tables

  • Create and Load Tables using SQL Scripts

• Intermediate SQL

  • Refining your Results

    • String Patterns, Ranges, Sorting, and Grouping

  • Functions, Multiple Tables, and Sub-queries

    • Built-in Database Functions

    • Sub-Queries and Nested SELECTS

    • Working with Multiple Tables

• Accessing Databases using Python

  • How to Access Databases Using Python

  • Writing Code using DB-API

  • Connecting to a Database Instance

  • Creating Tables, Inserting, and Querying Data

  • SQL Magic

  • Analysing Data with Python

• Course Assignment

  • Working with Real World Datasets

  • Getting Table and Column Details

  • Loading Data

• Bonus Module: Advanced SQL for Data Engineering

  • Views, Stored Procedures, and Transactions

    • Using Views

    • Stored Procedures

    • ACID Transactions

    • Committing and Rolling Back a Transaction

  • JOIN Statements

    • Join Overview

    • Inner Join

    • Outer Joins

🔑 Key Skills Learned

• Analysing data within a database using SQL and Python

• Creating relational databases on Cloud and working with tables

• Comparing and contrasting DDL to DML

• Writing SQL statements including SELECT, INSERT, UPDATE, and DELETE

• Generating joins to query data from multiple tables

🏆 Certificates

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