Every day, individuals are faced with a multitude of choices, ranging from selecting a product like orange juice or a car, determining who to vote for, to deciding on the most efficient mode of transportation for their daily commute. Professionals in various fields, such as marketers, retailers, product designers, political scientists, transportation planners, and sociologists, are keen on comprehending the underlying factors that drive these choices. To this end, choice models serve as valuable tools in predicting individuals' preferences based on the characteristics of the available options. Consequently, these models play a crucial role in informing significant product design decisions. This course aims to equip participants with the necessary skills to effectively analyze choice data, estimate choice models using the statistical programming language R, and effectively communicate their findings. The curriculum encompasses the examination of real-world choices, as well as the application of conjoint analysis, a survey-based approach, to understand decision-making processes. By the end of this course, students will possess the knowledge and expertise to organize choice data, employ statistical techniques to estimate choice models, and effectively present their research outcomes.