## January 2018

## Stata 1: Introduction to Stata

Note: Topics are subject to change. Topics: Basics – Interfacing with Stata, Do-files, getting help. Working with Data Sets – Importing, opening, and saving data files. Data Management – Getting…

## October 2018

## Data management in R with data.table

Matt Dowle, author of the data.table package, describes it as, “provid a high-performance version of base R's data.frame with syntax and feature enhancements for ease of use, convenience and programming speed.” In this workshop…

## November 2018

## Regular Expressions II

Regular expressions are perfectly suited for people who like puzzles. Regular expressions are a sequence of characters used to define a search pattern. They are commonly used to do “find”…

## Web Scraping with Python

This workshop will provide an overview of how to scrape data from html pages and website APIs using Python. This will mostly be accomplished using the Python requests, beautifulsoup, retry…

## Spatial point process models

Spatial point (and marked point) process models help us analyze the geometrical pattern of points in space and find application in a variety of fields including image processing, public health,…

## January 2019

## Intro to SQL

Ever want to know how to communicate with a database? You need to know SQL, a standard programming language for working with relational database management systems in data warehouses or…

## Introduction to Stata

Topics: By the end of the workshop, participants will be able to: Work with Stata, including using Do-files and using the help system. Get data into Stata and manage your…

## February 2019

## Statistical Analysis with R

This is a two day workshop (February 4 and 5) in R which is a free and open source environment for data analysis and statistical computing. While R contains many…

## Introduction to Programming with Python & Matlab

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…

## Mixed Models with R

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…

## Python for Data Analysis

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)…

## Generalized Additive Models

Nonlinear relationships abound in nature, though typical statistical models ignore this in favor of simplicity, often at a cost of both predictive capabilities and better understanding of the underlying phenomenon…

## Introduction to Deep Neural Networks with Keras/TensorFlow

Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network libraries, including…

## March 2019

## Statistical Analysis with R

This is a two day workshop (March 4 and 5) in R which is a free and open source environment for data analysis and statistical computing. While R contains many…

## Latent Variable Modeling

Part of the Structural Equation Modeling (SEM) series. This workshop will help participants develop skills in understanding and conducting latent variable models, particularly from the perspective of structural equation modeling.…

## PySpark

Apache Spark is a powerful open source processing engine built around speed, ease of use, and sophisticated analytics. Industry has quickly adopted Spark and deployed it at scale for processing…

## Intro to Web Applications using Flask and Python

Ever want to build your own web application? Do you want to do it using Python? Well then, Flask is the answer you are looking for. Its a micro web…

## Introduction to Deep Neural Networks with Keras/TensorFlow

Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network libraries, including…

## Doing more with RStudio

This talk will serve as an demonstration of what RStudio can offer for those that do not use it, as well as a showcase for more advanced use for those…

## Introduction to Stata

Topics: By the end of the workshop, participants will be able to: Work with Stata, including using Do-files and using the help system. Get data into Stata and manage your…

## April 2019

## Sliding into Slurm: An early look at U-M’s new high-performance computing environment

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…

## Web Scraping with Python

This workshop will provide an overview of how to scrape data from html pages and website APIs using Python. This will mostly be accomplished using the requests, beautifulsoup, retry modules…

## Sliding into Slurm: An early look at U-M’s new high-performance computing environment

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…

## Sliding into Slurm: An early look at U-M’s new high-performance computing environment

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…

## May 2019

## Introduction to the Linux Command Line

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…

## Introduction to the Linux Command Line

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…

## Introduction to the Flux cluster and batch computing

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…

## Advanced batch computing on the Flux cluster

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…

## Introduction to the Flux cluster and batch computing

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…

## Introduction to the Great Lakes cluster and batch computing with Slurm

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…

## June 2019

## Advanced batch computing with Slurm on the Great Lakes cluster

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…

## R package demo: gganimate and patchwork

This brief workshop will demonstrate the capabilities of two recent R packages, gganimate and patchwork. One package allows the data explorer to provide some lively enhancement to an otherwise static…

## Introduction to Stata

Topics: By the end of the workshop, participants will be able to: Work with Stata, including using Do-files and using the help system. Get data into Stata and manage your…

## July 2019

## More Mixed Models

In the R world, lme4 is a great package for mixed model estimation, and the most widely used for such models. For standard settings, few tools will do the trick…

## Spin Class: No Sweat Reports in R

If you use R, there’s a decent chance you are already familiar with using Rmarkdown files and the knitr package to create reports documenting your analyses. A lesser known but…

## August 2019

## Introduction to the Great Lakes cluster and batch computing with Slurm

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…

## September 2019

## Research Computing on the Great Lakes cluster

## Research Computing on the Great Lakes cluster

## Introduction to Deep Neural Networks with Keras/TensorFlow

Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network…

## Introduction to the Linux Command Line

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…

## Research Computing on the Great Lakes cluster

## Introduction to the Linux Command Line

## Introduction to SPSS

Audience: Never before SPSS users who will be using SPSS for Windows. Those using SPSS for Unix or Macintosh should email the instructor at cpow@umich.edu before enrolling. Fundamentals This portion introduces SPSS…

## Introduction to Stata

Audience: Those who have never used Stata before but wish to learn. By the end of the workshop, participants will be able to: Work with Stata, including using Do-files and…

## Research Computing on the Great Lakes cluster

## October 2019

## Web Scraping with Python

This workshop will provide an overview of how to scrape data from html pages and website APIs using Python. This will mostly be accomplished using the requests, beautifulsoup, and retry…

## Introduction to NumPy (Python)

This workshop will introduce you to the NumPy library in Python, which is useful in scientific computing. We will cover NumPy’s n-dimensional array object and associated functions in depth, along…

## Back to a Future: Asynchronous Computing with futures in R

Asynchronous computing is an umbrella term encompassing parallel and concurrent computational programs in which some tasks can be executed without a strict sequential order. A future is a programming abstraction for a value…

## Mediation Models: A demonstration using multiple packages

Mediation models are commonly applied in a variety of modeling settings, and people will typically flock to tools specific to structural equation modeling like Mplus or Amos for analysis. However,…

## Research Computing on the Great Lakes Cluster

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…

## November 2019

## Intro to SQL

Ever want to know how to communicate with a database? You need to know SQL, a standard programming language for working with relational database management systems in data warehouses or…

## Introduction to Deep Neural Networks with Keras/TensorFlow

Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network…

## Programming with R

People using R for applied research are often not taught basic programming practices such as writing functions, efficient iterative processing, vectorization, and other practices that would make their research far…

## Rcpp: Integrating C++ into R

The Rcpp package for R provides “seamless R and C++ integration”. In this workshop, we will discuss the use of Rcpp to speed up existing R code by rewriting slow functions…

## Research Computing on the Great Lakes Cluster

## December 2019

## Intro to D3.js for data visualization

D3.js is a JavaScript library for producing dynamic, interactive data visualizations in web browsers. It makes use of the widely implemented SVG, HTML5, and CSS standards. We’ll explore how to…

## January 2020

## Introduction to Deep Neural Networks with Keras/TensorFlow

Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network…

## Introduction to the Linux Command Line

## Research Computing on the Great Lakes Cluster

## Advanced research computing on the Great Lakes cluster

OVERVIEW This workshop will cover some more advanced topics in computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and…

## Introduction to the Linux Command Line

## Research Computing on the Great Lakes Cluster

## Advanced research computing on the Great Lakes cluster

OVERVIEW This workshop will cover some more advanced topics in computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and…

## Intro to SQL

Ever want to know how to communicate with a database? You need to know SQL, a standard programming language for working with relational database management systems in data warehouses or…