## August 2016

## Data Science Skills Series week 1

Fast data processing with Go We will demonstrate basic Go using several practical examples of data manipulation. Go (golang.org) is an open source programming language that has many syntax features…

## Data Science Skills Series Week 2

Data processing and visualization in R This workshop will delve into common data processing and exploration techniques, especially as a prelude to visualization. The main focus will be the dplyr…

## September 2016

## Data Science Skills Series Web Scraping with Python

Web Scraping with Python We will provide an overview of how to scrape data from html pages and website APIs using Python. For demonstration purposes, we will scrape sports and…

## Determining Sufficient Sample Size

This workshop outlines how to calculate an appropriate sample size (n) to address the objectives of a research project. Participants will be led through essential steps for the design of…

## October 2016

## Machine Learning in Python (Scikit-Learn)

This workshop will cover the essentials of unsupervised machine learning algorithms using Python's Scikit-learn library. We will focus on K-Means and Principal Component Analysis (PCA). The workshop is designed for intermediate to advanced…

## Exploring Your Data with R

R is an extremely powerful tool for data modeling, visualization, and general programming. In many practical applications of statistics, the vast majority of time is spent preparing the data for…

## November 2016

## Geospatial image processing with Google Earth Engine

Google Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. This class will give a gentle introduction to the power and convenience of…

## Location Analysis with ArcGIS and Python

Scope: Location analysis plays a central role in a variety of situations such as identifying potential breeding areas for mosquitoes, finding the best path for emergency evacuation, demarcating suitable area…

## January 2017

## Regular expressions

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”…

## Data science with social science data

This workshop covers the essential steps to data analysis in Python, using social science data as a case study. The workshop is divided into two parts. The first session includes an introduction to Python’s…

## Structural Equation Modeling I: Graphical Models

This workshop will help participants develop skills in understanding graphical models, and specifically from the perspective of structural equation modeling (SEM). After a general overview of concepts, regression approaches with…

## Data science with social science data

This workshop covers the essential steps to data analysis in Python, using social science data as a case study. The workshop is divided into two parts. The first session includes an introduction to Python’s…

## Introduction to SPSS

This workshop is 2 sessions Audience: Never before SPSS users who will be using SPSS for Windows. Those using SPSS for Unix or Macintosh should email the instructor at jerrick@umich.edu before enrolling. Note:…

## February 2017

## Structural Equation Modeling II: Latent Variables

This workshop will help participants develop skills in understanding and conducting latent variable models, and specifically from the perspective of structural equation modeling. After a conceptual overview, a broad view…

## Statistical Analysis with R

This is a two day workshop in R which is a free and open source environment for data analysis and statistical computing. While R contains many built-in statistical procedures, a…

## Structural Equation Modeling III

This workshop will help participants develop skills in understanding and conducting structural equation models. After an initial review of path analytic and measurement model techniques with latent variables (covered in…

## Matlab II

MatLab is a powerful tool for solving engineering and scientific problems. This session is designed for participants who have some experience with the basic operations but would like to expand…

## March 2017

## 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…

## Data Science with Social Science data: An introduction to Pandas and StatsModels in Python

This workshop introduces participants to Python’s NumPy, Pandas DataFrames, Matplotlib and StatsModels using an advertising dataset. Participants will use these tools to model (OLS) associations between advertising expenditures and product…

## April 2017

## Data Science with Social Science data: building predictive models using Python’s Scikit-learn

We will use Python’s Pandas DataFrames, Matplotlib and Scikit-learn to analyze census data. Participants will use Scikit-learn tools to predict whether income exceeds a particular dollar amount based on the census data. This workshop covers…

## Introductory GIS

This workshop will cover introductory GIS concepts, tools, and techniques. We will use ArcGIS (and QGIS) and learn basics of GIS by solving specific problems. You will also learn to…

## Generalized Additive Models

This workshop will introduce participants to generalized additive models (GAM) as a means to extend their efforts beyond the usual glm setting. In addition, extensions and connections to other models…

## Create Thematic Maps with Python

Everybody loves maps. Learn how to create thematic maps in Python using matplotlib for export for use in reports and publications. We’ll cover how to produce the most common thematic…

## May 2017

## Fitting General Linear and Mixed-Effects (Multilevel) Models in SPSS®

This three-half-days (May 22, 23, 24) workshop is designed to provide experienced SPSS users (please read prerequisites below carefully) with hands-on exposure to more advanced modeling techniques in SPSS, using…

## June 2017

## Data Visualization, Analysis and Modeling with JMP Pro

JMP is an easy-to-use, standalone statistics and graphics software from SAS Institute. It includes comprehensive capabilities for every academic field, and its interactive point-and-click interface and linked analyses and graphics…

## 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…

## Interactive data visualization using Bokeh in Python

Come learn how to make interactive data visualization using Bokeh in Python. Bokeh was designed to help people quickly and easily create interactive plots, dashboards and data applications. We’ll cover…

## July 2017

## Collecting Data from Social Media APIs using Python

Social media is a rich source of data for social scientists and data scientists. We’ll cover how to use the APIs from leading social media sites including Facebook, Google and…

## August 2017

## A Primer to Python I

The majority of our data science Python workshops require basic knowledge of Python. This two-part workshop is aimed to provide you with that basic knowledge that is needed for these…

## A Primer to Python I

The majority of our data science Python workshops require basic knowledge of Python. This two-part workshop is aimed to provide you with that basic knowledge that is needed for these…

## A Primer to Python II

The majority of our data science Python workshops require basic knowledge of Python. This two-part workshop is aimed to provide you with that basic knowledge that is needed for these…

## A Primer to Python II

## Data Visualization, Analysis and Modeling with JMP Pro

JMP is an easy-to-use, standalone statistics and graphics software from SAS Institute. It includes comprehensive capabilities for every academic field, and its interactive point-and-click interface and linked analyses and graphics…

## Data Visualization, Analysis and Modeling with JMP Pro

JMP is an easy-to-use, standalone statistics and graphics software from SAS Institute. It includes comprehensive capabilities for every academic field, and its interactive point-and-click interface and linked analyses and graphics…

## Programming: best practices

This workshop will introduce participants to several good programming practices. Topics include: proper use of identifier names and comments; self-documenting code; modularization; use of tests and assertions; debugging, profiling code; and version control. For demonstration…

## September 2017

## Geospatial Analysis with Google Earth Engine – I

Google Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. This class will give a gentle introduction to the power and convenience of…

## Pandas Dataframes: Data Processing and Visualization in Python

This workshop will delve into common data processing and exploration techniques. We will use NumPy, Matplotlib and Pandas to perform data exploration in Python. Among others, we’ll demonstrate how to…

## Image Processing – I

If you use image data in your work, but are not trained to analyze it, this workshop could be for you. This is a hands-on workshop where I will cover…

## October 2017

## Data Science with Social Science data: an introduction to Pandas and StatsModels in Python

This workshop introduces participants to Python’s NumPy, Pandas DataFrames, Matplotlib and StatsModels using an advertising dataset. Participants will use these tools to model (OLS) associations between advertising expenditures and product…

## Intro to SQL

Do you need to communicate with a database? Well, you need to know SQL, a standard programming language for working with relational database management systems in data warehouses or just…

## Introduction to MATLAB

This workshop introduces participants to MATLAB. Topics include indexing and slicing of vectors and matrices, creation of script M-files and functions, control flow operators and basic 2D and 3D visualization.…

## Debugging and Profiling R code

This workshop will provide suggestions and concrete advice on debugging R code, informally (tactics to be used) and formally (using commands such as "traceback" and "debug"). We'll also discuss preventing…

## Supervised Machine Learning: Random Forests

This workshop will introduce participants to Supervised Machine Learning (SML) and Random Forests (RFs) using Python’s Scikit-learn library. We’ll start with a brief explanation of Anaconda and the Jupyter notebook…

## Data Science with Social Science data: building predictive models using Python’s Scikit-learn

We will use Python’s Pandas DataFrames, Matplotlib and Scikit-learn to analyze census data. Participants will use Scikit-learn tools to predict whether income exceeds a particular dollar amount based on the…

## November 2017

## Data Processing with R

This talk will delve into common data processing and exploration techniques. The main focus will be on packages that enhance and facilitate the sorts of operations that typically arise when…

## Image Processing – II

Building upon the first workshop, we will cover more low level techniques such as opening, closing, edge detection, texture analysis, segmentation, and will start frequency domain processing. I will try to…

## Text Processing and Analysis with R

This workshop will cover the basics of text processing in R, such as string manipulation, dealing with factors, using regular expressions, etc. In addition, a case study of analysis, e.g.…

## Issues in Analysis of Complex Sample Survey Data

This 2-half day workshop will provide participants with an introductory overview of issues frequently encountered when conducting secondary analyses of data collected from sample surveys with complex multi-stage designs (e.g.…

## Supervised Machine Learning: Support Vector Machines (SVMs)

This workshop will introduce participants to Supervised Machine Learning (SML) and Support Vector Machines (SVMs) using Python’s Scikit-learn library. We’ll start with a brief explanation of Anaconda and the Jupyter…

## Visualization in R

Visualizing the results of research is a key aspect in facilitating scientific communication to a broad audience. The focus of this workshop will be on using common tools in R…

## December 2017

## Record Linkage in Python

Record Linkage is defined as the task of finding records within or between data sources that refer to the same entity. This workshop will introduce participants to the Python Record…

## Regular Expressions

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”…

## January 2018

## Making Web Maps with Google Fusion Tables

Fusion Tables is an experimental data visualization web application (launched in 2009) to gather, visualize, and share data tables. You can create web maps (e.g. dot maps, choropleths, heat maps)…

## Regular Expressions

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”…

## SPSS I Introduction to SPSS

Note: Topic order is subject to change. This workshop is designed to introduce participants to SPSS. It will cover the fundamentals of SPSS, within-case transformations, data management with multiple files,…

## Regular Expressions II

## Introduction to MATLAB

This workshop introduces participants to MATLAB. Topics include indexing and slicing of vectors and matrices, creation of script M-files and functions, control flow operators and basic 2D and 3D visualization.…

## February 2018

## Pandas Dataframes: Data Processing and Visualization in Python

This workshop will delve into common data processing and exploration techniques. We will use Pandas to perform data exploration in Python. Among others, we’ll demonstrate how to load data files,…

## 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…

## Data Science with Social Science data: an introduction to Pandas and StatsModels in Python

This workshop introduces participants to Python’s NumPy, Pandas DataFrames, Matplotlib and StatsModels using an advertising dataset. Participants will use these tools to model (OLS) associations between advertising expenditures and product…

## SEM Series I: Graphical Models

This workshop will help participants develop skills in understanding graphical models, and specifically from the perspective of structural equation modeling (SEM). After a general overview of concepts, regression approaches with…

## Data Processing with R

This talk will delve into common data processing and exploration techniques. The main focus will be on packages that enhance and facilitate the sorts of operations that typically arise when…

## Data Science with Social Science data: building predictive models using Python’s Scikit-learn

We will use Python’s Pandas DataFrames, Matplotlib and Scikit-learn to analyze census data. Participants will use Scikit-learn tools to predict whether income exceeds a particular dollar amount based on the…

## Applied Survival Analysis POSTPONED

This 2-day workshop (PLEASE NOTE: THIS WORKSHOP HAS BEEN POSTPONED) covers basic concepts and common analytical approaches for time-to-event data, known variously as survival analysis (in biological and medical sciences), event history…

## SEM Series II: Latent Variables

This workshop will help participants develop skills in understanding and conducting latent variable models, with particular from the perspective of structural equation modeling. After a conceptual overview, a broad view…

## Factor analysis and related techniques (with demonstrations in R)

This workshop will expose participants to a variety of related techniques that might fall under the heading of 'factor analysis', latent variable modeling, dimension reduction and similar, such as principal…

## March 2018

## SEM Series III: Structural Equation Models

This workshop will help participants develop skills in understanding and conducting structural equation models. After an initial review of path analytic and measurement model techniques with latent variables (covered in…

## Introduction to R Markdown

This workshop will introduce participants to the basics of R Markdown. After an introduction to concepts related to reproducible programming and research, demonstrations of standard markdown as well as overviews…

## Introduction to Network Analysis using igraph

Networks can represent a variety of things: social connections, roads, the world wide web, political donations, etc. Networks are most commonly known from social network analysis but they also exist…

## 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…

## Deep Neural Networks with TensorFlow: A Quick Start Introduction

Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. TensorFlow is a popular software library that is often used to construct and train DNNs. In this workshop,…

## Machine Learning: Concepts and Application

Machine learning can be described as a form of data analysis, often even utilizing well-known and familiar techniques, that has bit of a different focus than traditional analytical practice in…

## Making Web Maps with Google Fusion Tables

Fusion Tables is an experimental data visualization web application to gather, visualize, and share data tables. You can create web maps (e.g. dot maps, choropleths, heat maps) in a matter…

## Parallel Processing with Python

Modern computers have a CPU with multiple cores (usually between 4-8). Come learn how to take advantage of them to parallelize and speed up your code. We’ll show you how…

## May 2018

## Intro to Natural Language Processing with Python

This workshop will provide a quick overview of natural language processing using Python. We’ll cover the basics. Segmenting text into tokens, assigning part-of-speech, assigning dependency labels, detecting and labeling named-entities.…

## Data Processing in Python using Pandas

This workshop will introduce participants to Python’s Pandas. We’ll start with a brief explanation of Anaconda and the Jupyter notebook environment (although not required for the participant, the instructor will…

## Statistical Analysis with R

This is a two day workshop (May 21 & 22) in R which is a free and open source environment for data analysis and statistical computing. While R contains many…

## Geospatial analysis with Google Earth Engine

Google Earth Engine (GEE) combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. This workshop will provide an introduction to GEE. We will cover data…

## Introduction to R Markdown

This workshop will introduce participants to the basics of R Markdown. After an introduction to concepts related to reproducible programming and research, demonstrations of standard markdown as well as overviews…

## 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. Note: Topic order is subject…

## June 2018

## 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,…

## Classification, Regression and Model Selection using Python’s Scikit-learn

This workshop will introduce participants to machine learning in Python. We’ll start with a brief explanation of Anaconda and the Jupyter notebook environment (although not required for the participant, the…

## 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

This is the first workshop in a series of three workshops that will cover spatial modeling of three broad classes of data: (i) spatial point pattern, (ii) discrete spatial variation…

## July 2018

## Exploring the Tidyverse

This talk will delve into common data processing and exploration techniques within the tidyverse family. The main focus will be on packages that enhance and facilitate the sorts of operations…

## MoRe

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…

## August 2018

## Visualization in R

Visualizing the results of research is a key aspect in facilitating scientific communication to a broad audience. The focus of this workshop will be on using common tools in R…

## CSCAR Intro to Programming (Session 1 – Python)

This workshop is designed for students with no programming experience that are registered, or would like to register in courses that require basic programming skills. Non-students are welcomed to register…

## CSCAR Intro to Programming (Session 2 – Python)

This workshop is designed for students with no programming experience that are registered, or would like to register in courses that require basic programming skills. Session 1,2,3: Introduction to Python and…

## Intermediate SQL

This workshop is a continuation of the Intro to SQL class by CSCAR. We’ll cover how to create a table schema, how to insert data into tables and some more…

## CSCAR Intro to Programming (Session 3 – Python)

This workshop is designed for students with no programming experience that are registered, or would like to register in courses that require basic programming skills. Session 1,2,3: Introduction to Python and…

## CSCAR Intro to Programming (Session 4 – Matlab)

This workshop is designed for students with no programming experience that are registered, or would like to register in courses that require basic programming skills. (Matlab)

## September 2018

## MoRe

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…

## November 2018

## Dimension Reduction Techniques

This workshop will provide an overview of commonly used dimension reduction techniques such as principle components analysis (PCA), multi-dimensional scaling (MDS), and factor analysis. The focus will be on concepts…

## August 2019

## Research Computing on the Great Lakes cluster

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…

## September 2019

## 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…

## 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…

## January 2020

## R I: Data Wrangling

This workshop will delve into common data processing and exploration techniques using R. The main focus will be on constructing and manipulating R data objects, and using packages that enhance…

## R by Example: Analyzing RECS using tidyverse

In the R by Example series of workshops, we’ll discuss example analyses in R as a vehicle for learning commonly used tools and programming patterns. The “Analyzing RECS using tidyverse” workshop will…

## February 2020

## R by Example: Analyzing RECS using data.table

In the R by Example series of workshops, we’ll discuss example analyses in R as a vehicle for learning commonly used tools and programming patterns. The “Analyzing RECS using data.table” workshop will…