Log in

Sign up for our mailing list!

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., 24-Jun-19
E.g., 24-Jun-19
May 23, 2019
Author:
Kari Peterson

Take your visualization to the next level. We'll review:

  • Joining vs Blending

  • Parameters

  • Containers in dashboards

  • Stories

  • Actions

  • Level of Detail calculations

May 16, 2019
Author:
Evan Muzzall

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.

May 16, 2019
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.

May 15, 2019
Author:
Evan Muzzall

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:

May 15, 2019
Author:
Véronique Irwin

This three-part series will cover the following materials:

Part 1:  Introduction

May 14, 2019
Author:
Evan Muzzall

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:

May 14, 2019
Author:
Ilya Akdemir

This three-part series will cover the following materials:

Part 1:  Introduction

May 13, 2019
Author:
Evan Muzzall

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:

May 13, 2019
Author:
Hero Ashman

This three-part series will cover the following materials:

Part 1:  Introduction

May 10, 2019
Author:
Drew Hart

Raster data are used to represent geographic phenomena that are present and can be measured anywhere in a study area, like elevation, temperature, rainfall, land cover, soil type, etc. These data are a valuable resource for social scientists, planners, and engineers as well as natural scientists. This workshop will introduce basic raster concepts and methods for working with raster data in R.

May 9, 2019
Author:
Evan Muzzall

R Fundamentals Part 4: Putting it all together

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.

May 9, 2019
Author:
Drew Hart

Geospatial data are an important component of social science and humanities data visualization and analysis. The R programming language is a great platform for exploring these data and integrating them into a research project. 

Geospatial Data in R, part 2: Geoprocessing and analysis

May 8, 2019
Author:
Evan Muzzall

R Fundamentals Part 3: Data Exploration and Analysis

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.

May 8, 2019
Author:
Patty Frontiera

Geospatial data are an important component of social science and humanities data visualization and analysis. This workshop will introduce basic methods for working with geospatial data in Python using GeoPandas, a relatively new Python library for working with geospatial data that has matured and stabilized in the last few years.

May 7, 2019
Author:
Josué Meléndez Rodríguez

Qualitative Data Analysis (QDA) software is used to organize and structure data, codes, memos, and other components of a qualitative study.

This workshop is a two-part series for qualitative researchers,  new and established, interested in learning about MAXQDA, a QDA software for which D-Lab provides substantive support.

May 7, 2019
Author:
Evan Muzzall

R Fundamentals Part 2: Subsetting and Reshaping

May 7, 2019
Author:
Josué Meléndez Rodríguez

Qualitative Data Analysis (QDA) software is used to organize and structure data, codes, memos, and other components of a qualitative study.

This workshop is a two-part series for qualitative researchers,  new and established, interested in learning about MAXQDA, a QDA software for which D-Lab provides substantive support.

May 7, 2019
Author:
Drew Hart

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

Geospatial Data in R, part I: Getting started with spatial data objects

May 6, 2019
Author:
Josué Meléndez Rodríguez

This session focuses on explaining the proces of creating, organizing, and applying codes within the context of qualitative research. An overview of qualitative data analysis (QDA) software will be provided, noting general advantages and disadvantages, as well as comparing popular programs. Participants will also be introduced to analysis using QDA software.

May 6, 2019
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!

Pages