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“When you go out and talk to other people, you realize that you become the opposite of being siloed. You really start to realize that you might have been in an echo chamber when you were talking amongst your own colleagues, and when you start to hear other people, you go, Oh, there’s more that I could understand.”

Today, we speak with Rachel Saidi, Professor in the Math, Statistics, and Data Science Department and Data Science Program Director at Montgomery College, a two-year college outside Washington, DC. Rachel shares her path from teaching math to statistics to data science, and what it’s like to scale a data science program in the community college setting, with the goal of catering to students of all ages and experiences. She tackles holistic data science education, combining curriculum, experiential learning, speaker series, and more, while also acknowledging difficulties with constraints like faculty capacity and transfer articulation with four-year universities. Finally, she reflects on how professional organizations can help educators find community and stay on top of best practices, and offers advice to educators and learners on how to tackle data science teaching and learning today.

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