## Past Events › Data Science Skills Series

### Events List Navigation

## November 2017

## 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…

## 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,…

## 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…

## 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…

## 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

## 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…

## May 2018

## 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…

## June 2018

## 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…

## 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…

## November 2018

## Matching with R

An introduction to matching, such as propensity score matching, using R's "optmatch" package. Matching is used to improve balance between groups, typically in observational studies, by creating quasi-experimental strata of similar individuals. We…