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Data today is being collected at unprecedented speed and scale. Everyday we create 2.5 quintillion bytes of data. In order to unlock the powerful potential of this big data, businesses need researchers and professionals skilled in data analytics. The role of a Data Scientist is to turn data into useful insights that can be used by businesses to take informed decisions.

If you are a data scientist or an aspiring data professional, you need to be comfortable working with SQL apart form other languages such as R,Python. Knowledge of SQL is incredibly important for big data professionals as much of the world’s raw data whether it is electronic medical records or customer transactions histories stored  in relational databases. Many organizations uses SQL to store and retrieve structured data. Therefore, to be an effective data scientist, one must know how to wrangle and extract data from relational databases using a language called SQL. Hence Data scientists need to be comfortable working with relational databases, especially SQL. If you want to play with data, you need some SQL.


As per KD Nuggets – “SQL is still one of the most important tools required, to be a successful data scientist,as the majority of data stored by businesses is in relational databases.”


  • Anyone who is interested in learning SQL
  • Anyone who is interested in learning SQL for Data Science

Course Curriculum

Course Introduction
1. Introduction 00:00:00
2. Course Curriculum Overview 00:00:00
3. Overview of Databases 00:00:00
6. Setup and Installation of PgAdmin and PostgreSQL 00:00:00
PostGreSQL Installation (Mac OS)
PostGreSQL Installation (Windows)
Databases and Tables
7. Databases and Tables Overview 00:00:00
8. Creating and Restoring a Database 00:00:00
9. Overview of Challenges! 00:00:00
10. Challenge: Restore a Database! 00:00:00
11. Restoring a Table Schema 00:00:00
12. Challenge: Restore a Table Schema! 00:00:00
13. Review of Section 00:00:00
SQL Statement Fundamentals
14. SQL Cheat Sheet 00:00:00
15. SQL Statement Fundamentals 00:00:00
16. SELECT Statement 00:00:00
17. Challenge: SELECT task 00:00:00
18. SELECT DISTINCT 00:00:00
19. Challenge: SELECT DISTINCT 00:00:00
20. SELECT WHERE 00:00:00
21. Challenge: SELECT WHERE 00:00:00
22. COUNT 00:00:00
23. LIMIT 00:00:00
24. ORDER BY 00:00:00
25. BETWEEN 00:00:00
26. IN 00:00:00
27. LIKE 00:00:00
GROUP BY Statements
28. MIN MAX SUM and AVG 00:00:00
29. GROUP BY 00:00:00
30. HAVING 00:00:00
31. Overview of JOINS 00:00:00
32. AS Statement 00:00:00
33. Overview of Inner Join 00:00:00
34. Examples of Inner Joins 00:00:00
35. Overview of Join types 00:00:00
36. Example of Outer Joins 00:00:00
37. Union 00:00:00
Advanced SQL Commands
38. Overview of Advanced SQL Commands 00:00:00
39. Timestamps and Extract 00:00:00
40. Mathematical Functions 00:00:00
41. String Function and Operators 00:00:00
42. SubQuery 00:00:00
43. Self-Join 00:00:00
Case Study 01 - Website Visitor Analysis
Case Study - Insurance Claim Analysis
Case Study - Ranking Products & Sales of a Ecommerce Dataset
Quiz 01
Quiz 02

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