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 […]
Overview 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 […]
This workshop will cover dimension reduction techniques for data analysis in Python, focusing on Principal Component Analysis (PCA), factor analysis, and canonical correlation analysis (CCA). Depending on audience interest, dimension reduction regression (e.g. SIR), and kernel versions of the classical dimension reduction techniques can also be discussed. The presentation will begin by covering the conceptual […]
This lecture-format workshop will present an overview of available modes and methods of survey data collection as well as an introduction to the survey response process and implications for questionnaire design. Participants will gain an appreciation of the tradeoffs inherent in survey design decisions and how design can affect data quality and survey errors. Topics […]
This workshop is designed for those who are interested in getting started with their own research and analytics of Twitter data. The workshop introduces workflows for using the Twitter API for programmers and non-programmers alike. For non-programmers, we'll be using the Postman software. For programmers, we'll demonstrate the same process in Python. We will also […]
Simulation studies are used to understand the properties of statistical procedures. This technique is widely used when conducting power analysis for research studies, which is one focus for this workshop. Simulation studies can also be used to assess the performance of statistical procedures in non-standard settings, such as when there are concerns about missing data, […]
This workshop will cover introductory GIS concepts, tools, and techniques. We will use QGIS (and ArcGIS) and learn the basics of vector- and network-data GIS by solving problems. You will also learn to generate maps. We will use the graphical user interface and no programming experience is required for this workshop. The workshop is meant for […]
OVERVIEW This workshop will provide a brief overview of the components of the Great Lakes 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 […]
This workshop will cover techniques for conducting large-scale inference, using Python and its libraries. We will cover the principals of how large scale inference is different from classical inference, and why multiple comparisons should usually be accounted for in an analysis. We will then discuss the Bonferroni method, Benjamini and Hochberg's False Discovery Rate (FDR), […]
OVERVIEW This workshop will cover some more advanced topics in cluster computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and basic use of Great Lakes; dependent and array scheduling; troubleshooting and analysis; a brief introduction to workflow scripting using bash; parallel processing in one […]