## 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…

## 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…

## January 2018

## 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

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”…

## 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.…

## March 2018

## 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,…

## 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…

## 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 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…

## 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…