Gain the fundamental SQL skills you need to interact with and query your data.
SQL is a powerful language used by data-driven businesses, large and small, to explore and manipulate their data to extract meaningful insights. In this track, you'll learn the SQL fundamentals you need to level up your data skills.
Through hands-on exercises, you’ll discover SQL basics, such as how to structure and query relational databases. As you progress, you’ll use these foundations to quickly summarize and join tables and use window functions and built-in PostgreSQL functions to analyze your data.
By the time you finish this track, you’ll have a firm understanding of the SQL essentials and have the confidence to apply them to your own data sets. You’ll be able to start working on a variety of SQL projects and develop your data science portfolio.
Overview
Syllabus
- Introduction to SQL
- Learn how to create and query relational databases using SQL in just two hours.
- Intermediate SQL
- Accompanied at every step with hands-on practice queries, this course teaches you everything you need to know to analyze data using your own SQL code today!
- Analyzing Students' Mental Health
- Joining Data in SQL
- Level up your SQL knowledge and learn to join tables together, apply relational set theory, and work with subqueries.
- Data Manipulation in SQL
- Master the complex SQL queries necessary to answer a wide variety of data science questions and prepare robust data sets for analysis in PostgreSQL.
- PostgreSQL Summary Stats and Window Functions
- Learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon!
- Functions for Manipulating Data in PostgreSQL
- Learn the most important PostgreSQL functions for manipulating, processing, and transforming data.
- Database Design
- Learn to design databases in SQL to process, store, and organize data in a more efficient way.
- Impact Analysis of GoodThought NGO Initiatives
Taught by
Mona Khalil, Fernando Gonzalez Prada, Michel Semaan, Brian Piccolo, Lis Sulmont, Izzy Weber, Jasmin Ludolf, and Maham Khan
