Unit testing is an essential component of every data science project, offering numerous advantages such as saving valuable development and maintenance time, enhancing documentation, fostering end-user confidence, and minimizing downtime of productive systems. Consequently, unit testing has become an indispensable skill in the industry, widely adopted by nearly all companies. This comprehensive course focuses on teaching unit testing in Python, utilizing the highly popular pytest testing framework. By the conclusion of this course, participants will have successfully constructed a comprehensive test suite for a data science project. Throughout the course, individuals will gain proficiency in writing unit tests for data preprocessors, models, and visualizations. Additionally, participants will acquire the ability to interpret test results and rectify any faulty code. Advanced concepts, including Test-Driven Development (TDD), test organization, fixtures, and mocking, will also be covered, equipping individuals with the necessary skills to effectively test their own data science projects.