Object detection is a fundamental task of computer vision that is constantly evolving, with a wide range of applications in fields such as security, medicine, and autonomous driving. This work presents an interactive self-learning course dedicated to exploring some crucial concepts for beginners in object detection. The course offers educational resources, including the possibility to follow a simple tutorial on the operation of an object detection model and definitions of the main concepts related to object detection technology. Users also have a brief description of object detection algorithms such as YOLO (You Only Look Once), R-CNN (Region-based Convolutional Neural Networks), and SSD (Single Shot Detector) and the possibility to learn more about these in a tutorial prepared on a Google Colab notebook. The course aims to provide a learning experience accessible to beginners in the field of object detection, who want to take the first step in their learning about the subject. After completing the tutorial, the user answers a questionnaire, with the goal of analyzing the learning outcomes and extracting the user’s impression of the website in general. With this paper, we want to show the advantages of using tools of this nature to foster learning regarding object detection.