This paper presents the design and preliminary results of a low cost self-driving cars project based course for undergraduate students, which aims to integrate automotive design concepts, localization and navigation algorithms, computer vision, and deep learning techniques. This course is part of the Mechatronics program at Pontificia Universidad Catolica del Peru (PUCP), and was inspired by the growth in demand of intelligent/autonomous cars in the automotive industry. The main objective of the course is to provide the basic concepts of automation technologies in the area of autonomous cars and provide the fundamental tools for the development of self-driving cars. In order to achieve this, the students must complete a course compose of five theoretical modules (39 hours), and five practical modules (10 hours), during an entire semester at PUCP. The course promotes undergraduate students to work as a team, learn from hands-on experience, validate their prototypes in real scenarios, and learn basic scientific writing and presentation skills. The preliminary results show that the students enrolled in the course learned the necessary concepts to implement a low cost self-driving car capable of driving autonomously inside a two lanes racetrack and avoid obstacles by changing lanes only using a camera, an embedded system and ultrasonic sensors for the mapping, path planning and obstacle detection algorithms.