Data Science Dojo Sensei Package

Mentoring Terms and Conditions

The Data Science Dojo mentoring offering is a means for our students to expand and deepen the knowledge and skills they acquire from the bootcamp. Students form small teams and are paired with an experienced data scientist from industry as a mentor. The student team then tackles a public Kaggle competition with the advice of their mentor. Typically, students that get the most value from the mentoring offering have the following two characteristics: 1) The student has the ability to dedicate 8-10 hours a week post-bootcamp on the Kaggle competition. 2) The student could benefit from additional intensive hands-on work (e.g., the student’s current job doesn’t offer sufficient data science opportunities).

The following are the Terms & Conditions for students registered for Data Science Dojo Sensei package mentoring option.

1. All students must engage the mentoring offering within 60 days of the end of their respective bootcamp.

2. Students are responsible for organizing teams of 4-5 prior to requesting the assignment of a mentor. Students may use the following Data Science Dojo resources for communication:

a. In-class solicitation during the bootcamp.

b. The applicable Slack channel.

c. The Data Science Dojo alumni LinkedIn group.

3. Student teams have access to their mentor as follows:

a. Up to 5 total hours of the mentor’s time distributed as the team sees fit.

b. A total of 60 continuous days from when the initial meeting of the team and the mentor occurs.

4. Working with their mentor, the student team is required to select an appropriate Kaggle competition with the following characteristics:

a. Allows Kaggle teams (some competitions allow only solo competitors).

b. Has a minimum of 30 days left before completion, ideally 60 days left for completion.

c. Students can select competitions with more than 60 days until completion, but mentoring stops at the 60-day mark.

5. Students are required to handle all project management-related aspects of the mentoring experience. Examples include, but shall not be limited to:

a. Forming teams.

b. Requesting a mentor assignment once team is formed.

c. Establishing work assignments, regular meeting cadence, Kaggle teams, etc.

d. Building any required technical infrastructure (e.g., GitHub, cloud VMs, etc.).

6. Students are required to craft all code for the competition – the mentor’s purpose is to advise, not to be an active member of the student team.

7. In the event that, despite best efforts, a student team cannot be successfully formed (e.g., not enough Sensei students in a cohort), Data Science Dojo has the option to change the Terms & Conditions as needed to accommodate. Examples include, but are not limited to:

a. Lengthening the time requirement between the end of a student’s bootcamp and the beginning of mentoring.

b. Lowering the number of required students for a team.