Transition to Python & Interviews

Dhaval Patel

Data Entrepreneur | YouTuber | Ex - Bloomberg, Nvidia

I have 17 years of experience in Programming and Data Science working for big tech companies like NVIDIA and Bloomberg. I also run a famous YouTube channel called Codebasics where I pursue my passion for teaching. Codebasics is one of the top channels on YouTube when it comes to data science, machine learning, data structures, etc. I firmly believe that “Anyone can code” and I use analogies, simple explanations, and step-by-step storytelling to explain difficult concepts in such a way that even a high school student can understand them easily.

Hemanand Vadivel

Ex- Data Analytics Manager, 8+ Years in Europe, Microsoft Certified, Certified Supply Chain Professional

I’m a mechanical engineer who transitioned to a full time Data & Analytics manager in the UK & Germany by teaching myself Power BI, excel & anything else that was required to solve the problem. I have worked with complex data across Supply Chain, Sales, Marketing, Revenue Management, Finance and HR functions over the last 8 years to deliver effective solutions. To me, Analytics is an extra sensory organ that anyone can develop to become a superhuman at work. I have conducted several workshops and internal training to help non-technical people to become superhuman at work and now, really excited for this opportunity to share all that knowledge with you in this course.

Transition to Python & Interviews

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Contents

1: Welcome to The SQL Experience

1.1: Course Outline

1.2: How Learning SQL can Help You in Your Career

1.3: Who is Peter Pandey?

1.4: Peter Pandey’s Early Life and SQL

2: Course Overview

2.1: Who can Enroll in this Course? Any Prerequisites?

2.2: What Type of Computer do I Need for this Course?

2.3: Course Outline

3: Welcome to The SQL Experience

3.1: How Learning SQL can Help You in Your Career

3.2: Who is Peter Pandey?

3.3: Peter Pandey’s Early Life and SQL

4: Enhance your Learning Experience

4.1: Setting Video Resolution and Video Speed Globally

4.2: Join Discord

5: SQL Basics: Data Retrieval - Single Table

5.1: Install MySQL: Windows

5.2: Install MySQL: Linux, Mac

5.3: Import Movies Dataset in MySQL

5.4: Retrieve Data Using Text Query (SELECT, WHERE, DISTINCT, LIKE)

5.5: Exercise - Retrieve Data Using Text Query (SELECT, WHERE, DISTINCT, LIKE)

5.6: Retrieve Data Using Numeric Query (BETWEEN, IN, ORDER BY, LIMIT, OFFSET)

5.7: Exercise - Retrieve Data Using Numeric Query (BETWEEN, IN, ORDER BY, LIMIT, OFFSET)

5.8: Summary Analytics (MIN, MAX, AVG, GROUP BY)

5.9: Exercise - Summary Analytics (MIN, MAX, AVG, GROUP BY)

5.10: HAVING Clause

5.11: Calculated Columns (IF, CASE, YEAR, CURYEAR)

5.12: Exercise - Calculated Columns (IF, CASE, YEAR, CURYEAR)

5.13: The Data God’s Blessing

5.14: Quiz

5.15: Chapter Summary

6: SQL Basics: Data Retrieval - Multiple Tables

6.1: Why do We Need Multiple Tables?

6.2: SQL Joins (INNER, LEFT, RIGHT, FULL)

6.3: Exercise - SQL Joins (INNER, LEFT, RIGHT, FULL)

6.4: Cross Join

6.5: Analytics on Tables

6.6: Join More Than Two Tables

6.7: Exercise - Join More Than Two Tables

6.8: Quiz

6.9: Chapter Summary

7: SQL Basics: Complex Queries

7.1: Subqueries

7.2: ANY, ALL Operators

7.3: Co-Related Subquery

7.4: Exercise: Subqueries

7.5: Common Table Expression (CTE)

7.6: CTE Benefits & Other Applications

7.7: Exercise: CTE

7.8: Peter Pandey Flexes his SQL Skills

7.9: Quiz

7.10: Chapter Summary

8: SQL Basics: Database Creation & Updates

8.1: Database Normalization and Data Integrity

8.2: Entity Relationship Diagram (ERD)

8.3: Mentor Talk: Art of Googling

8.4: Data Types: Numeric (INT, DECIMAL, FLOAT, DOUBLE)

8.5: Data Types: String (VARCHAR, CHAR, ENUM)

8.6: Data Types: Date, Time (DATETIME, DATE, TIME, YEAR, TIMESTAMP)

8.7: Data Types: JSON, Spatial (JSON, GEOMETRY)

8.8: Luck Favors the LinkedIn Post

8.9: Primary key

8.10: Foreign Key

8.11: Create a Database From an Entity Relationship Diagram - ERD

8.12: Import Data From a CSV File Into a Database

8.13: Insert Statement

8.14: Update and Delete

8.15: I Need a Favour

8.16: Expect the Unexpected: The Intermission Scene

8.17: Quiz

8.18: Chapter Summary

9: AtliQ Hardware & Problem Statement

9.1: The Rise of Databases at AtliQ

9.2: Relational vs No-SQL Database

9.3: AtliQ Hardware’s Business Model

9.4: Profit & Loss Statement

9.5: ETL, Data Warehouse, OLAP vs OLTP, Data Catalog

9.6: Fact vs Dimension Table, Star vs Snowflake Schema, Data Import