PostgreSQL For Data Science And Data Analyst

 2Month/20 Hours                                                  Price: 40,000

                                                                                     35,000

PostgreSQL For Data Science And Data Analyst

SQL for data analysis refers to the database querying language’s ability to interact with multiple databases at once and its use of relational databases. SQL is one of the most commonly used and flexible languages.

In this course, you’ll learn how to read and write complex queries to a database using one of the most in-demand skills. These skills also apply to any other major SQL database, such as MySQL, Microsoft SQL Server, Amazon Redshift, Oracle, and much more.

Learning SQL is one of the fastest ways to improve your career prospects as it is one of the most in-demand tech skills! In this course, you’ll learn quickly and receive challenges and tests along the way to improve your understanding!

---

What you’ll learn

• Write complex SQL statements to query the database and gain critical insight into the data
• The transition from the Very Basics to a Point Where You can Effortlessly Work with Large SQL Queries
• Learn Advanced Querying Techniques
• Become a Master SQL Developer

---

Course Content:

Module1:Introduction

Course Overview

---

Module2: Database Basics:

What is a Database
How to Proceed in this Course
Install Postgres Database on Ma
Troubleshoot Connection
Install Postgres on Window
Create Table and Insert a Statement
Prepare the Database
Assignment 1: Create More Tables and Populate Data

---

Module3: SQL Query Basics

Filter Data Using the WHERE Clause + AND & OR
WHERE Clause and Operators
ORDER BY, LIMIT, DISTINCT and Renaming Columns
Assignment 2: Practice Writing Basic Queries (5 Problems)

---

Module4:Using Functions:

UPPER(), LOWER(), LENGTH() + Boolean Expressions & Concatenation
String Functions: SUBSTRING(), REPLACE()
Grouping Functions: MIN(), MAX(), AVG(), SUM(), COUNT()

Assignment 3: Practice with Functions, Conditional Expressions and Concatenation

---

Module5: Grouping Data:

Understanding Grouping
GROUP BY & HAVING Clauses
 GROUP BY and HAVING Clauses
Assignment 4: Practice Aggregation Queries

---

Module6: Using Subqueries:

Aliasing Sources of Data
Introducing Subqueries
Subqueries with ANY and ALL Operators
Assignment 5: Practice with Subqueries

---

Module7: Using Case Clause:

Conditional Expressions Using CASE Clause
Transposing Data using the CASE Clause
Assignment 6: Practice Using Case and Transposing Data

---

Module8: Advanced Query Techniques using correlated Subqueries

Understanding Correlated Subqueries

Correlated Subqueries Continued

---

Module9:Working with Multiple Tables

Introducing Table Join
INNER and OUTER Joins
Using UNION, UNION ALL, and EXCEPT Clauses 
Cartesian Product with the CROSS JOI
[EXERCISES]: Joins and Subqueries Continued
Creating Views vs. Inline View

Assignment 7: ADVANCED Problems using Joins, Grouping and Subqueries

---

Module10: Window Functions for Analytics

 Window Functions using the OVER() Clause
Ordering Data in Window Frame
RANK, FIRST_VALUE, and NTILE Functions
Working with LEAD and LAG Function

Working with Rollups and Cubes

---

INTERNATIONAL STUDENT FEE 250$ USD