Instruction is more than lecture the Lead Instructor demos a new concept by sharing the screen with the class on a large projector, and leads an interactive discussion on the subject. People from both coding tracks are welcome! This course is intended to bring everyone together as we wrap up our bootcamps.During the Live Training, the Lead Instructor flips back and forth between instruction and exercises. Note that you must be registered for another bootcamp course to join. We will be diving into random forests and neural networks. Demystifying Machine Learning (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.The last day will be an overview of campus resources and useful tools to help make grad school easier. 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. This series aims to help incoming PhD students make the transition. Life During Grad School (Sep 12 – Sept 15, 3:00 pm – 4:15 pm CT): Starting grad school is always a big leap.The focus is on practical application and therefore will include extensive coding exercises. Topics include modern approaches to regression, time series modeling, and Bayesian statistics. Over the course of the bootcamp, we will develop a toolkit of methods students will likely need to complete their own research. Statistics for Research (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.Computing for Research (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.Introduction to Scientific Programming (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.Our 2022 program includes the following sessions:
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