ENVIRONMENTAL DATA SCIENCE BOOTCAMPS
We’re hosting our 5th annual “Environmental Data Science Bootcamps” (Aug 29 – Sept 16)! These free bootcamps will be occurring in a hybrid format with the option of being in-person or remote.
The September bootcamps introduce relevant computational and statistical tools. They are intended to give new and continuing PhD students a jumpstart into the practical skills needed for conducting research. The courses are hosted and organized by our current DSEER fellows. Lessons are applicable to a wide range of fields, but examples will be drawn from environmental sciences.
Applications are closed! Decisions will be sent out soon.
The calendar listed below is our 2022 schedule:
Our 2022 program includes the following sessions:
- Introduction to Scientific Programming [Python workshop] (Aug 29 – Sep 14, 9:30 am – 12:30 pm CT): For those new to programming, a Python course in the basics to get you up to speed: variables, arrays, list, for loops, if statements, functions, and how to work with NumPy, Pandas, and Matplotlib for basic data sciences purposes.
- Computing for Research [Python workshop] (Aug 29 – Sep 7, 9:30 am – 12:30 pm CT): For those who already know the programming basics, this Python course will dive into more advanced computational methods, including data exploration and visualization, using the computing cluster, version control software (Git), and working with geodata formats.
- Statistics for Research [R workshop] (Sep 8 – Sep 14, 9:30 am – 12:30 pm CT): This R course provides a broad overview of useful statistical techniques used in scientific research. Over the course of the bootcamp, we will develop a toolkit of methods students will likely need to complete their own research. Topics include modern approaches to regression, time series modeling, and Bayesian statistics. The focus is on practical application and therefore will include extensive coding exercises.
- Life During Grad School [Panelist series] (Sep 12 – Sept 15, 3:00 pm – 4:15 pm CT): Starting grad school is always a big leap. This series aims to help incoming PhD students make the transition. The first three days will be panels where senior grad students and faculty will discuss topics like navigating the student-advisor relationship and work-life balance. The last day will be an overview of campus resources and useful tools to help make grad school easier. Snacks will be provided!
- Demystifying Machine Learning [Python mini workshop] (Sep 15 – Sep 16, 9:30 am – 12:30 pm CT): This session aims to make machine learning more approachable by removing some of the mystery. We will be diving into random forests and neural networks. Note that you must be registered for another bootcamp course to join. People from both coding tracks are welcome! This course is intended to bring everyone together as we wrap up our bootcamps.