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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 


Job Interview Preparation  (Soft Skills Questions & Answers)


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Internships, Freelance and Full-Time Work opportunities


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Microsoft SQL Server Database Administration Course

Oracle SQL Database Expert

MySQL Database (for Beginners)

Big Data Analytics Course

Data Sciences Specialization

Diploma in Big Data Analytics

Big Data + Data Sciences Training 

KEY FEATURES

Flexible Classes Schedule

Online Classes for out of city / country students

Unlimited Learning - FREE Workshops

FREE Practice Exam

Internships Available

Free Course Recordings Videos

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