This course provides comprehensive instruction on leveraging PostgreSQL for effective management of date and time data. Participants will gain proficiency in utilizing functions and calls to efficiently parse, manipulate, and calculate with this data, as well as employ window functions for enhanced analysis. The curriculum also covers working with time series data, encompassing a range of date and time data types and techniques for seamless conversion between them. Participants will learn to manipulate granularity, perform calculations, including aggregations, partitioning, and running averages. These skills will enable them to derive valuable insights from existing time series data. Furthermore, the course delves into the practical application of time series analysis to real-world datasets. Participants will have the opportunity to analyze temperature data, examine train schedules, and explore the temporal dynamics of news article popularity. By engaging with these real-world examples, participants will develop a deeper understanding of how to effectively apply time series analysis techniques in various contexts.