Overview

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this comprehensive course, you will master SQL and its application in data analysis, equipping you with the essential skills to extract valuable insights from databases. Beginning with foundational database concepts, you'll progress through various SQL commands and queries, focusing on real-world problem-solving. You'll learn to create and manage databases, tables, and schemas while understanding key concepts such as primary and foreign keys, indexes, and partitions. The course is structured in two levels. Level 1 covers essential database operations, from data retrieval using SELECT queries to complex filtering and sorting techniques. In Level 2, you’ll advance into combining data from multiple tables, working with subqueries, and applying window functions for in-depth analysis. By the end of the course, you’ll be confident in using SQL for data manipulation, transformation, and analysis. This course is ideal for aspiring data analysts and anyone looking to gain practical SQL skills. There are no specific prerequisites, though basic understanding of data structures will be helpful. This course is suitable for beginners and those looking to enhance their data analysis toolkit.

Syllabus

Course Introduction

In this module, we will introduce the course and its content. You will understand the importance of learning SQL for data analysis and get a brief overview of the course structure and objectives.

Getting Started!

In this module, we will kick off with Level 1 of the course, where you will learn about the foundational role of SQL in data analysis, understand the course roadmap, and set up PostgreSQL for your learning environment.

Databases - Terminology

In this module, we will cover the fundamental terminology and concepts related to relational databases, including tables, keys, schemas, and indexing strategies to improve query performance.

SQL - Creating Databases, Schemas, and Tables

In this module, we will focus on creating and organizing databases, schemas, and tables. You will also learn how to manipulate data with essential SQL commands like INSERT, UPDATE, and DELETE.

SQL - Retrieving Data with Queries

In this module, we will dive into SQL queries, focusing on retrieving data using SELECT statements. We will cover filtering, sorting, and grouping techniques to enhance your data retrieval skills.

Course Summary - Level 1

In this module, we will summarize the key learnings from Level 1 and highlight how these concepts will be foundational for the more advanced topics covered in the next level of the course.

Introduction to Level 2

In this module, we will introduce the second level of the course, where you will dive deeper into advanced SQL concepts and learn how to apply them to real-world data analysis challenges.

Getting Started with Level 2

In this module, we will get you started with Level 2 by providing you with the necessary datasets and objectives. You'll learn to load them into PostgreSQL and get a preview of the more complex topics ahead.

SQL - Combining Data from Multiple Tables

In this module, we will explore how to combine data from multiple tables using SQL operators and join techniques. You will learn how to merge datasets and analyze complex data relationships.

SQL – Subqueries

In this module, we will dive into subqueries, learning how to use them to extract valuable insights from data. We will explore various types of subqueries and demonstrate their usage in different SQL clauses.

SQL - Conditional Logic (CASE)

In this module, we will explore SQL’s CASE expression, a powerful tool for transforming and classifying data. You will learn how to apply conditional logic to create flexible and dynamic query results.

SQL - Window Functions

In this module, we will explore window functions, which allow for advanced analysis across data partitions. You will learn how to use window functions for ranking, sequencing, and analyzing data in complex ways.

SQL – Simplify Queries (Views, CTEs)

In this module, we will explore techniques to simplify complex SQL queries using Views and Common Table Expressions (CTEs), enhancing both query performance and readability.

Course Summary - Level 2

In this module, we will summarize the key learnings from Level 2 and discuss how these advanced SQL techniques will help you in your data analysis projects going forward.