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“We're all used to tracking changes in Word, so why wouldn't we want to have something like that for our code? And we're all used to Google Docs where we can collaborate in real time, so why wouldn't we want to be doing that with our code too? So both for keeping track of changes and for facilitating collaboration, anyone who I work with, I mentor them in using GitHub”

Welcome to Season 10! To kickoff our new season, we sit down with Jade Benjamin-Chung, an Assistant Professor at Stanford University in the Department of Epidemiology and Population Health, to talk about her journey into public health and becoming a leader in reproducible data science practices. Throughout the episode, we discuss the creation of her lab manual outlining best practices in data science, mentoring in low-resource settings, and promoting ethical data practices.

“If a student isn't able to be part of data collection, then I really encourage them to build a relationship with a local collaborator who knows the data really deeply. For example, I'll have a student who is really bright with coding, but has less experience working with real world data sets. I'll have them pair up with someone from, say, Bangladesh, where I do a lot of research, and they'll kind of mentor them in coding…and the person working in Bangladesh will mentor them in the data”

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“I never thought I would find that sense of community here, especially as a transfer, because I've heard so much about the stereotypes…I think a club really helped combat that” —Avani Gireesha

In our final episode of Season 9, we hear from three graduating UC Berkeley seniors, all of whom transferred from California community colleges into the Data Science major: Avani Gireesha, Hannah Brown, and Jake Pastoria. They reflect on their transitions from community college to Berkeley, discussing the clubs, research, and experiences they’ve gained in their two years here. Listen in as they offer advice for incoming transfer students on how to prepare academically, find community, and get the most out of their Berkeley experience!

“I'm still not really used to the exam rigor here and how difficult it is, but that's totally okay. I feel challenged here, and it really pushes me to get out of my comfort zone and be a better student” —Hannah Brown

“I think these classes change the way that I view education as a whole…I'll never forget opening up my first Data 8 Jupyter notebook and submitting it. Education here is really cool, and I think you should take all these classes, especially when the professors are absolute legends in Berkeley and just computer science and data science in general” —Jake Pastoria

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“There's a famous quote by a statistician, John Tukey, who's often associated with sort of introducing and promoting the concept of exploratory data analysis. And his quote is that the best thing about being a statistician is that you get to play in everyone's backyard, by which he means, as a data scientist, you get to dabble in all of these different areas…the longer you work in statistics, data science and adjacent fields, you really start to see that all these stories around data that come up in different disciplines, they're actually linked through the language of statistics and mathematics. So when I start a new domain, I will usually try to start by reasoning by analogy” —Prof. Alex Franks

In this week’s episode, we talk with Professors Mike Ludkovski and Alex Franks from UC Santa Barbara about their diverse research backgrounds—ranging from stochastic modeling to sports analytics—and how they shaped their approach to data science education. Mike and Alex discuss the value of co-teaching, designing interdisciplinary curriculum, and helping students connect theory to real-world practice. They also touch on some major initiatives aimed at expanding access to data science education, including the Southern California Consortium and the Pacific Alliance for Low-Income Inclusion.

“We found out… the awareness of data science is vastly different across campuses within just a few miles of each other… we are trying to help different places stand up data science courses, programs, and share best practices. We organize events like datathons for high school and community college students” —Prof. Mike Ludkovski