## 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 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 for Windows, the…

## February 2020

## Introduction to Matlab

This workshop will introduce you to Matlab. We will look at general coding syntax, matrix operations, writing functions, symbolic capabilities, etc. Computers will be available to complete exercises.

## R II: Programming

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…

## Introduction to SAS: Basic Data Manipulating, Summarizing, and Graphing

Prerequisites: Familiarity with basic statistical calculations and graphs is helpful. In this one-day, six-hour workshop we will discuss the basics of using SAS for data analysis. The workshop is held…

## R by Example: Functional Programming with dplyr

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 “Functional Programming with dplyr” workshop will…

## 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…

## R III: Modeling

This workshop will be heavy on conceptual understanding of basic regression modeling, but with demonstration of activities both essential and tangential to good modeling practice. GLM, model interpretation, model comparison,…

## March 2020

## Introduction to Python’s NumPy library

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…

## R by Example: Functional Programming with 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 “Functional Programming with dplyr” workshop…

## Introduction to SAS: Simple Inference Procedures

Prerequisites: Participant should have some familiarity with introductory statistics and be able to load data into and perform basic data manipulations in SAS. In this one-day, six-hour workshop we will…

## 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”…

## Machine Learning in R

In this workshop, we’ll first discuss core machine learning concepts such as: choosing loss functions and evaluation metrics; splitting the data into training, validation, and testing sets; and cross-validation patterns…

## 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…