Where this course comes from
In an earlier video Nitish shared a complete SQL roadmap and a list of resources, and promised an end-to-end SQL course. This video keeps that promise: about six hours of SQL taught specifically for data science.
- It is a recording of a live course he taught at a college earlier that year, so you will hear students asking questions and see him answering them. The tone is interactive.
- He works through many MCQs during the class, and uses real-world datasets, such as a movies dataset and the Titanic dataset, so you can relate to what you are querying.
- The whole course uses MySQL as the database.
What it covers
The course is more than SQL syntax. It also teaches database fundamentals: why we use databases at all, the important concepts (keys, integrity, ER diagrams), and what a DBMS does for you.
Python + MySQL
Build a small CRUD app (register / login) to see a database in action.
Database theory
Data vs information, files vs databases, DBMS, relational model, integrity.
Keys
Super, candidate, primary, alternate, foreign, composite, compound, surrogate.
SQL command types
DDL, DML, TCL, DCL, plus data types, operators and comments.
ER diagrams
Design a database (Swiggy example) before you build it.
Queries
DDL, DML, GROUP BY, CASE, joins and subqueries.
How to study it
Short on time? Focus only on the SQL query parts: DDL, then DML, GROUP BY, CASE, joins and subqueries.
Watch the whole thing end to end. The theory (keys, integrity, ER diagrams) is what makes your queries and table designs correct, and it is asked in interviews too.
Nitish's answer: if you finish this course and then practise a lot of SQL problems, you should be ready for most data-science job interviews. Watch the video, then go and solve plenty of practice questions; that is what makes it stick.
The course also shows how to connect a database to Python and run SQL from code. Many courses skip this as unimportant, but Nitish feels every data scientist should know how an application actually talks to a database. That is the next chapter.
Course map with timestamps
| # | Chapter | Starts at | Notes |
|---|---|---|---|
| 1 | Introduction | 0:00 | This page |
| 2 | CRUD App using Python and MySQL | 3:00 | Notes |
| 3 | Database Theory | 50:00 | Notes |
| 4 | Database Keys | 1:23:00 | Notes |
| 5 | Types of SQL commands | 1:51:00 | Notes |
| 6 | ER Diagram | 1:57:30 | Notes |
| 7 | DDL SQL Queries | 2:18:20 | Notes |
| 8 | DML SQL Queries | 3:00:00 | Notes |
| 9 | GROUP BY Query | 4:08:00 | Notes |
| 10 | CASE Statement | 4:42:00 | Notes |
| 11 | SQL Joins | 4:48:00 | Notes |
| 12 | Subquery | 5:25:35 | Notes |
The dataset used in the course is linked in the video description.
Conceptual questions
These check whether you understand why, not just what. Several go one step beyond the video.
Why does the course teach database theory (keys, ER diagrams, integrity) and not only SQL syntax?
Syntax tells you how to ask; theory tells you what a correct design looks like. Both are tested.
You know SELECT, joins and GROUP BY syntax well but have solved very few problems. According to the course's advice, what's the biggest gap?
The course is the foundation; fluency comes from practising lots of problems afterwards.