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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.