Your instructor: Noah Snyder-Mackler
Noah Snyder-Mackler is an assistant professor in Arizona State University’s School of Life Sciences and the Center for Evolution and Medicine. He holds a PhD in the psychology of animal behavior.
“I'm in the biology department and a lot of my work centers on trying to understand how our lived experiences or our environment gets under the skin to affect how our cells and our brain function at the molecular level using a lot of genomic tools and techniques. High dimensional sorts of things, to ultimately impact our health, how we age and how long we live,” said Snyder-Mackler.
How you’ll learn
You’ll learn how to work the Studio R program and analyze the grammar and vocabulary used in the R programming language. You’ll also discover how to "wrangle" your big data, understand it, synthesize it and visualize it in a way that conveys what you want to your audience. To do this, you’ll watch walk-through videos before jumping in and experiencing the process for yourself.
“It's really learning by doing for the most part because biology and the data that we're generating are so diverse, there isn’t a one-size-fits-all approach for the students,” said Snyder-Mackler. “I want to give you the skills to know what to do next based on where you are now. To use that really old adage, I'm not just giving students a fish, I'm trying to teach them to fish.”
What makes this course special
You’ll develop your skills by working hands-on with real world data or your own research data, ultimately preparing you for the next steps in your current course of study and future career.
“I think the best way that anyone can learn is by doing the data analysis and working with their own data, or data that they feel some connection to or responsibility for. Students can come into this class and find a data set that they're excited about,” said Snyder-Mackler.
What you’ll get out of BIO 591
At the BIO 591, you’ll be able to effectively digest, synthesize, interpret, visualize and present very complex and large data sets.
“I'm teaching these students what I think is a really useful skill,” said Snyder-Mackler. “Even if they just get to scratch the surface of learning this language, they at least get to take home some broader messages about being good data stewards and good data interpreters, good data consumers.”