This is a four-part workshop introducing programming concepts to those with little-to-no programming experience. The four 2-hour sessions will take place over two weeks, with Python being taught in the first three sessions, and Matlab in the fourth session. Computers are provided. Session 1: Feb 6, 11am - 1pm - Location: MLB 2001a Session 2: […]
Mixed models are an extremely useful modeling tool for situations in which there is some dependency among observations in the data, where the correlation typically arises from the observations being clustered in some way. For example, it is quite common to have data in which we have repeated measurements for the units of observation, or […]
This workshop will provide a brief overview of the the new HPC environment and is intended for current Flux and Armis users. We will use the temporary Beta HPC cluster to demonstrate how jobs will be submitted and managed under the new Great Lakes, Armis2, and Lighthouse clusters available later this year. There are […]
This workshop will provide a brief overview of the components of the Flux Cluster. The main body of the workshop will cover the resource manager and scheduler, creating submissions scripts to run jobs and the options available in them, and hands-on experience. By the end of the workshop, every participant should have created a submission […]
We'll discuss mixed model regression (also known as multi-level models or hierarchical linear models) in this session which is used for repeated measures data or data which has a clustering element. We'll start with a theoretical overview, discuss choosing an appropriate model, fitting the models, checking assumptions and post-hoc analysis. We'll also cover diagnosing convergence […]
This course will cover some more advanced topics in cluster computing on the U-M Flux Cluster. Topics to be covered include a review of common parallel programming models and basic use of Flux; dependent and array scheduling; advanced troubleshooting and analysis using checkjob, qstat, and other tools; and parallel debugging and profiling of C and […]
This course will familiarize the student with the basics of accessing and interacting with Linux computers using the GNU/Linux operating system’s Bash shell, also generically referred to as “the command line”. Topics include: a brief overview of Linux, the Bash shell, navigating the file system, basic commands, shell redirection, permissions, processes, and the command environment. […]
Learn data analysis with Python. We’ll be using pandas, the go-to Python library used for data wrangling and analysis. We’ll be practicing with several different real-world datasets (e.g. time-series, text) and learning how to read, write, clean, transform, merge and reshape data. The workshop is intended for users with basic Python knowledge. Anaconda Python 3.6 […]
Multilevel modeling is the state-of-the-art approach for handling data with complex dependence structure in a regression analysis. This workshop will discuss fitting multilevel models in Python using the Statsmodels package. We will discuss the motivation and main use cases for multilevel modeling, and illustrate by example how to fit linear and generalized linear mixed models. […]
Do you have experience in working alongside community partners in data analysis or program evaluation? Do you want to connect with others who are using their skills for public good? National efforts from organizations such as DataKind, Data Science for Social Good, and Statistics without Borders have been expanding in recent years as more individuals […]