Time is a constraint when it comes to assigning ML projects and supervising them (by the teaching faculty) at the same time. With the help of Clouderizer console, the university faculty members can make use of the shared templates (within Community section) and set up the project infrastructure (skipping the DevOps stage) and assign it to all students at once. Students, on the other hand, can clone and complete their projects using the same pre-emptive Clouderizer console and submit it. These assignments can later be reviewed by the faculty member or TA. Hence, Clouderizer enables the teaching faculty to focus more on lectures and tests, for the time and effort to create and assign an ML or data science project is reduced tremendously. Analytics feature gives a strong insight into every homework and assignment as how many students cloned the project and the duration of run time by every student.