Master SQL For Data Science

BY
Udemy

Become thoroughly familiar with the concepts and methodology associated with SQL for a variety of data science activities.

Mode

Online

Fees

₹ 649 4099

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

SQL is required for handling structured data by a data scientist. Considering that relational databases are used to store structured data. Therefore, a data scientist needs to be well-versed in SQL commands to query these databases. Master SQL For Data Science certification course is designed by Imtiaz Ahmad - Senior Software Engineer & Trainer, which is delivered by Udemy for learners who wish to master the fundamentals of data science using the features of the structured query language.

Master SQL For Data Science online classes encompasses 9 hours of video-based learning materials along with 4 downloadable study resources and assignments that are intended to offer learners a foundation in SQL and dealing with data so they can start analyzing it for data science applications. Master SQL For Data Science online course covers the fundamentals of SQL statements, SQL queries, CASE clauses, window functions, and advanced querying methods including aggregations, subqueries, rollups, cubes, joins, transposing & ranking data, and using conditional expressions.

The highlights

  • Certificate of completion
  • Self-paced course
  • 9 hours of pre-recorded video content
  • 12 articles 
  • 4 downloadable resources
  • Assignments

Program offerings

  • Online course
  • Learning resources
  • 30-day money-back guarantee
  • Unlimited access
  • Accessible on mobile devices and tv

Course and certificate fees

Fees information
₹ 649  ₹4,099
certificate availability

Yes

certificate providing authority

Udemy

What you will learn

Data science knowledge Sql knowledge

After completing the Master SQL For Data Science online certification, learners will develop an in-depth understanding of the fundamentals of data science using the capabilities of SQL. in this data science course, learners will explore the functionalities of SQL statements, SQL queries, subqueries, CASE clauses, views, tables and window functions. In this SQL certification, learners will study strategies involved with aggregation and grouping data.

The syllabus

Database Basics

  • What is a Database
  • How to Proceed in this Course
  • Dedicated TA Support
  • Install Postgres Database on Mac
  • Troubleshoot Connection
  • Install Postgres on Windows
  • Create Table and Insert Statements
  • Data file that will be used in the course (IMPORTANT)
  • Prepare the Database
  • Assignment 1: Create More Tables and Populate Data

SQL Query Basics

  • Introducing the SELECT Statement
  • Filter Data Using the WHERE Clause + AND & OR
  • Filtering Operators - IN, NOT IN, IS NULL, BETWEEN
  • [EXERCISES]: WHERE Clause and Operators
  • Using ORDER BY, LIMIT, DISTINCT and Renaming Columns
  • Assignment 2: Practice Writing Basic Queries (5 Problems)

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()
  • Assignment 3: Practice with Functions, Conditional Expressions and Concatenation

Grouping Data and Computing Aggregates

  • Understanding Grouping
  • GROUP BY & HAVING Clauses
  • [EXERCISES]: Using GROUP BY and HAVING Clauses
  • Assignment 4: Practice Aggregation Queries

Using Subqueries

  • Aliasing Sources of Data
  • Introducing Subqueries
  • Subqueries Continued + [EXERCISES]
  • Subqueries with ANY and ALL Operators + [EXERCISES]
  • [EXERCISES]: More Practice with Subqueries
  • Assignment 5: Practice with Subqueries

Using the CASE Clause in Interesting Ways

  • Conditional Expressions Using CASE Clause + [EXERCISES]
  • Transposing Data using the CASE Clause + [EXERCISES]
  • Assignment 6: Practice Using Case and Transposing Data

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
  • Assignment 7: ADVANCED Problems using Joins, Grouping and Subqueries

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

Difficult Query Challenges

  • Challenging Puzzles For the Brave
  • Get Access to All of my current and future courses!

Course Extras!

  • Bonus Lecture

Articles

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