Master SQL For Data Science at UDEMY Overview
Duration | 9 hours |
Total fee | ₹360 |
Mode of learning | Online |
Credential | Certificate |
- Overview
- Highlights
- Course Details
- Curriculum
- Faculty
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Master SQL For Data Science at UDEMY Highlights
- Earn a Certificate of completion from Udemy
- Learn from 4 downloadable resource and 11 articles
- Get full lifetime access of the course material
- Comes with 30 days money back guarantee
Master SQL For Data Science at UDEMY Course details
- For anyone who wants to break into the data analyst or data scientist role
- What is a Database
- Installing Postgres
- Creating Tables
- Select Statement
- Filtering Operators
- Learn the skills you need to extract critical insight from data sitting in a database
- There are over 100 puzzles scattered throughout the course with in-depth solutions providing plenty of opportunity for participants to practice
- Move step by step into more advanced topics as we delve into the world of advanced querying techniques using subqueries, aggregations, joins, rollups and cubes, window functions, transposing & ranking data and using conditional expressions in very interesting ways
Master SQL For Data Science at UDEMY Curriculum
Database Basic
What is a Database
How to Proceed in this Course
Dedicated TA Support
Install Postgres Database on Mac
Install Postgres on Windows
Create Table and Insert Statements
Prepare the Database
SQL Query Basic
Introducing the select statement
Filter Data Using the WHERE Clause + AND & OR
Filtering Operators- IN, NOT IN, IS NULL, BETWEEN
Using ORDER BY, LIMIT, DISTINCT and Renaming Columns
Using Functions
UPPER(), LOWER(), LENGTH(), TRIM() + Boolean Expressions & Concatenation
Career Advice
String Functions: SUBSTRING(), REPLACE(), POSITION() and COALESCE()
Grouping Functions: MIN(), MAX(), AVG(), SUM(), COUNT()
Grouping Data and Computing Aggregates
Understanding Grouping
Group by & Having Clauses
Using GROUP BY and HAVING Clauses
Using Subqueries
Aliasing Sources of Data
Introducing Subqueries
Subqueries Continued + [EXERCISES]
Subqueries with ANY and ALL Operators + [EXERCISES]
More Practice with Subqueries
Using the Case Clause in Interesting ways
Conditional Expressions Using CASE Clause + [EXERCISES]
Transposing Data using the CASE Clause + [EXERCISES]
Advanced Query Techniques using correlated subqueries
Understanding Correlated Subqueries
[EXERCISES]: Correlated Subqueries Continued
Working with multiple tables
Introducing Table Joins
INNER and OUTER Joins + [EXERCISES]
Using UNION, UNION ALL and EXCEPT Clauses + [EXERCISES]
Cartesian Product with the CROSS JOIN
[EXERCISES]: Joins and Subqueries Continued
Creating Views vs. Inline Views
Window Functions for Analytics
Window Functions using the OVER() Clause
Ordering Data in Window Frames
RANK, FIRST_VALUE and NTILE Functions
Working with LEAD and LAG Functions
Working with Rollups and Cubes
Master SQL For Data Science at UDEMY Faculty details
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