MENTORING IN BEHAVIORAL DATA SCIENCE

Prerequisites & course information

Requisites: Consent of instructor Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: Yes, unlimited number of completions Last Taught: Fall 2025 Learning Outcomes: 1. Explore multiple strategies for effective mentoring Audience: Graduate 2. Understand how to apply key areas of mentoring (aligning expectations, effective communication, ethical behavior, active listening, assessing understanding, constructive feedback, time management, etc.) Audience: Graduate 3. Develop skills for mentoring in behavioral data science Audience: Graduate 4. Collaborate and problem-solve with peers Audience: Graduate 5. Articulate mentor philosophy and personal development goals Audience: Graduate Learning Outcomes: 1. Explore multiple strategies for effective mentoring Audience: Graduate 2. Understand how to apply key areas of mentoring (aligning expectations, effective communication, ethical behavior, active listening, assessing understanding, constructive feedback, time management, etc.) Audience: Graduate 3. Develop skills for mentoring in behavioral data science Audience: Graduate 4. Collaborate and problem-solve with peers Audience: Graduate 5. Articulate mentor philosophy and personal development goals Audience: Graduate