Log in

Sign up for our weekly newsletter!

This is an archive of our past training offerings. We are looking to include workshops on topics not yet covered here. Is there something not currently on the list? Send us a proposal.

E.g., 13-Aug-20
E.g., 13-Aug-20
February 12, 2020
Author:
Emily Grabowski

This workshop introduces students to scikit-learn, the popular machine learning library in Python, as well as the auto-ML library built on top of scikit-learn, TPOT. The focus will be on scikit-learn syntax and available tools to apply machine learning algorithms to datasets.

February 12, 2020
Author:
Evan Muzzall

In the final part, we will review data importation, subsetting, and visualization. Students will then be given the majority of time to reproduce a workflow on two different datasets, ask questions, and review the solutions as a group.

February 11, 2020
Author:
Aniket Kesari

This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Part 3 Topics:

February 10, 2020
Author:
Pelagie Elimbi Moudio

Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with 'relational' or 'labeled' data both easy and intuitive. It enables doing practical, real world data analysis in Python.

In this workshop, we'll work with example data and go through the various steps you might need to prepare data for analysis.

We plan to cover:

February 10, 2020
Author:
Evan Muzzall

Students will be introduced to data exploration and analysis in R. You will learn how to summarize data and explore it with histograms, scatterplots, and boxplots. You will also be introduced to coding statistical data analysis via t-tests, analyses of variance, correlation, and linear regression.

February 7, 2020
Author:
Véronique Irwin

This three-part series will cover the following materials:

Part 1:  Introduction

February 7, 2020
Author:
Evan Muzzall

Machine learning often evokes images of Skynet, self-driving cars, and computerized homes. However, these ideas are less science fiction as they are tangible phenomena that are predicated on description, classification, prediction, and pattern recognition in data.

February 7, 2020
Author:
Evan Muzzall

Machine learning often evokes images of Skynet, self-driving cars, and computerized homes. However, these ideas are less science fiction as they are tangible phenomena that are predicated on description, classification, prediction, and pattern recognition in data.

February 6, 2020
Author:
Gloria Ashaolu

The Black Recruitment and Retention Center is a student initiated, AND entirely a student ran organization that was founded in 1983 as direct response to the removal of Black students from affirmative action policies and programs, including admissions consideration, early academic outreach programs, and retention services. 

 

Working Group Session: Data Scholars: Discovery
February 6, 2020
February 6, 2020
Author:
Aniket Kesari

This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Part 2 Topics:

Working Group Session: Data Scholars: Pathways
February 5, 2020
February 5, 2020
Author:
Isabelle Cohen

This three-part series will cover the following materials:

Part 1:  Introduction

February 5, 2020
Author:
Evan Muzzall

R Fundamentals Part 2: Subsetting and Reshaping

Working Group Session: Data Scholars: Foundations
February 4, 2020
February 4, 2020
Author:
Aniket Kesari

This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Part 1 Topics:

February 3, 2020
Author:
Hero Ashman

This three-part series will cover the following materials:

Part 1:  Introduction

February 3, 2020
Author:
Evan Muzzall

Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills for free at our R workshops!

January 31, 2020
Author:
Drew Hart

Geospatial data are an important component data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. 

Geospatial Data in R, part 3: Working with raster data

January 31, 2020
Author:
Evan Muzzall

Machine learning often evokes images of Skynet, self-driving cars, and computerized homes. However, these ideas are less science fiction as they are tangible phenomena that are predicated on description, classification, prediction, and pattern recognition in data.

Pages