This research full paper describes our experience in teaching parallel programming for students without previous knowledge of basic concepts of computing, comparing their levels of learning. The use of parallel software grew considerably in recent years due to the increasing availability of multi and many-core devices. The evolution of hardware and software resources collaborated for a remarkable computational processing power offered by parallel programs. However, parallel programming is taught usually in more advanced years of the undergraduate computer courses, due to its supposed prerequisites as sequential programming, operating systems, computer architectures and others. Postponing parallel programming teaching hinder students to apply parallelism other subjects, reducing the probability of these future professionals think on parallel solutions naturally. We executed 05 experiments teaching parallel programming subjects for 252 students. We analyzed whether students without prerequisites could learn parallel programming in the same level verified with students with prior computing knowledge. We used three different teaching methodologies: traditional, Problem Based Learning (PBL), and Team-Based Learning (TBL). The teaching and learning evaluation took into account such metrics: parallelism thinking of students, use of programming-model, correct output of the program, source-code readability and satisfaction of the students. The paper shows that it is possible to teach parallel programming to students without previous knowledge of computing, obtaining high scores and interest in such learning. Our results contribute positively to disseminate parallel programming, which is vital to extract performance from nowadays computers.