Please note: This workshop was originally scheduled for Tuesday, 3/21 at 1:00 to 4:00pm. Due to a power outage in Barrows Hall, it has been rescheduled for Thursday, 4/6 at 1:00 to 4:00pm. If you plan to attend this make-up session, please take a moment to complete a separate registration using the "Register for this training" button at the bottom of the page.
Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills at the free D-Lab R workshops!
The R FUN!damentals workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, import, export, manipulate, and visualize data, and learn to write shorthand functions of your code. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.
Each of the four parts is divided into a lecture-style format interrupted by short breaks, challenge problems, and discussions. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. No prior experience or background knowledge is required, except we recommend that you enroll in D-Lab’s Programming FUN!damentals workshop if you are unfamiliar with the command line.
Intermediate workshops teach data subsetting, reshaping, and visualization, creating markdown and interactive .HTML files, dimension reduction techniques, and function writing. Advanced workshops emphasize machine learning algorithm creation and implementation in the semi-canned ‘caret’, ‘SuperLearner’, and ‘H2O’ software libraries. Intermediate and advanced workshops require completion of R FUN!damentals Parts 1 through 4 or equivalent knowledge.
Part 4: For-loops and Functions
Students will learn how to write for-loops and functions in R. You will learn how to personalize functions via control structures such as ‘if’ and ‘else’. These learning objectives will be exemplified through introduction to the construction and graphical representation of Monte Carlo resampling simulations.
Knowledge requirements: R Fundamentals 1, 2, and 3 or equivalent
Registration note: To participate in multiple parts of this series, please be sure to register for each day separately.
