This course will prepare students to be effective teaching assistants, course developers, and/or peer consultants in the field of data science. Students will gain aptitudes and tangible skills that are rarely taught in classes, broadly applicable to all career paths, and appropriate to placing on a resume.

This is a hands-on course, focused on building skills through practice with support from instructors and minimal lecture format:

FOUNDATIONAL LESSONS BY BERKELEY EXPERTS
The first five meetings employ talks by experts, use anecdotal evidence, and present different scenarios on teaching and consulting situations. Later in the semester, there will be opportunities for refresher courses based on interest.

HANDS-ON TEACHING AND CONSULTING EXPERIENCE
All students will work in one of the following roles:

• Connector Assistant: help instructors of Data Science Connector courses to deliver and teach material in labs and office hours
• Curriculum Developer: work closely with faculty (both Data Science and non-Data Science) to create and deploy data science curriculum materials in IPython notebooks
• Data-Enabled Course Assistant: help instructors of upper-division Data-Enabled courses to deliver and teach material in labs and office hours
• Data Peer Consultant: offer peer-to-peer consulting, debugging, and tutoring for students working in data science across the Berkeley campus

Each week will include role-specific responsibilities as well as team check-ins for students to reflect collectively on progress, receive feedback and support, and work through challenges.

GRADING
The course is Pass / No Pass and will be assessed on attendance, written reflections, role-specific work, and final presentations. Questions about the expectations and structure of the written reflections and final presentation will be addressed during the first meeting. Students will not be permitted to pass the course if they have more than one unexcused absence or more than three excused absences.

This student led course is supported by collaboration between the University Library, D-Lab, and the Division of Data Sciences.

To enroll in the DeCal, students must apply and be accepted for a position with the Division of Data Sciences. Enrollment codes will be distributed when the positions are offered. All students who filled out an application but have NOT heard back from the division before the first DeCal session (Monday 8/27) should attend the session. Applications are considered on a *rolling basis*, meaning that applications are continuously reviewed in the order that they are received. Apply early for the largest variety of opportunities! Curriculum Developer and Course Assistant positions: learn more at bit.ly/ds-teams-apply and apply at the link below. Peer Consultants: students interested in peer consulting should attend the first DeCal session for application information.