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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., 17-Oct-18
E.g., 17-Oct-18
October 1, 2015
Coordinator:
Dillon Niederhut

Day 3 (analyzing data)

Students will be introduced to the principles behind the grammar of graphics and the general linear model. Students will understand the implementation of plotting in R. Students will be able to explore, summarize, and analyze data using R's implementation of exploratory and inferential data analysis.

October 1, 2015
Coordinator:
Dav Clark

Dav Clark invites you to join his Hacking Measurement seminar for a presentation by the global tech company Civil Maps on their 3D mapping technology.

September 30, 2015
Coordinator:
Juan Shishido

"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."

September 29, 2015
Coordinator:
Teddy Roland

This workshop will offer a gentle introduction to the Python programming language and the popular NLTK (Natural Language Toolkit) package that includes useful tools for literary study. Together we will explore tools that Prof.

September 25, 2015
Coordinator:
Kunal Marwaha

This workshop is a beginner's introduction to the basics of programming and data analysis with Python. You will learn the fundamentals (variables, loops, lists, functions) and practice with sample data files.

September 25, 2015
Coordinator:
Zawadi Rucks-Ahidiana

This workshop covers how to organize and analyze qualitative data in Atlas.TI. Both researchers new to qualitative methods and experienced qualitative researchers are encouraged to attend.

September 25, 2015
Coordinator:
Chris Kennedy

This is the first workshop in a 3-part Stata series offered at the D-Lab that includes: 1) Intro to Stata, 2) Data Analysis in Stata and 3) Stata Programming.

September 24, 2015
Coordinator:
Shinhye Choi

Day 2 (clean and tidy data)

September 23, 2015

This two-hour workshop will introduce address geocoding - the process of determining the geographic location of a street address. The first part of this workshop will be an introduction to the process of geocoding and the various online and desktop tools available for geocoding.

September 22, 2015
Coordinator:
Josh Pepper

Come learn how to build a map with your public health data! We’ll discus the basics of spatial data and talk about useful places to find health data. I’ll show examples of how simple (and complex) maps can improve your health-related research, advocacy and communication. Then we’ll spend the bulk of our time creating an example map together.

September 21, 2015
Coordinator:
Patty Frontiera

This workshop will provide an overview of resources at the D-Lab and elsewhere on campus for getting started with geographic data, spatial analysis and web mapping. Bring your questions and wish list for related workshops you would like to see at the D-Lab.

September 21, 2015
Coordinator:
Caroline Boyden

Designers and developers! Have you ever made a seemingly-simple change to your site’s CSS, only to discover later that it caused display problems in places you didn’t think to look at? Maybe that change to your mobile menu looks fine at 320px, but unexpectedly breaks at 600.

September 18, 2015
Coordinator:
Kunal Marwaha

An intro to the basics that instructors often assume you know, but that you probably never had good instruction on! After this course, you should be able to more easily start learning to program (e.g., in R or python), follow instructions and documentation online (e.g.

September 18, 2015
Coordinator:
Zawadi Rucks-Ahidiana

This introductory workshop will introduce attendees to the reason for using a qualitative data analysis package for the coding and analysis process.  We will begin by discussing the distinction between coding and analysis, the benefits of using a QDA package, and then view a brief demonstration of a specific program.

September 17, 2015
Coordinator:
Dillon Niederhut

The R for Data Science workshop series is a four part course, designed to take novices in the R language for statistical computing and produce programmers who are competent in finding, displaying, analyzing, and publishing data in R.

Day 1 (basics of R)

September 14, 2015 to September 16, 2015
Coordinator:
Nick Adams

This INTENSIVE offers an introduction to a range of Text Analysis approaches, including dictionary methods, classification and machine learning, TF-IDF, clustering, and topic modeling. Tutorials are performed in R with RStudio.

Day 1: Introduction to text analysis approaches. What is automated text analysis? What questions can we ask and answer using these approaches?

September 11, 2015
Coordinator:
Zawadi Rucks-Ahidiana

The D-Lab's Qualitative Methods Group (QMG) invites current graduate students who are actively working with qualitative data this semester (collecting, analyzing, or writing about qualitative data) to meet other graduate students interested in forming a support group.  These Qualitative Research Support Groups serve as a source of accountability, trouble shooting, and writing groups depending o

September 10, 2015
Coordinator:
Jenny Palomino

Join the Qualitative Methods Group (QMG) for a conversation with Dr. Alice Kelly and Ms. Jenny Palomino about conducting mixed methods research with interview and spatial data.  Dr. Kelly and Ms. Palomino will discuss how they ended up merging interview and spatial methods for their project, and the challenges and successes of working with both types of data.

August 27, 2015 to August 29, 2015
Coordinator:
Sendhil Mullainathan

Registration CLOSED: LECTURES ARE FULL

This mini-course introduces machine learning tools to empirically knowledgeable economists  and other social scientists. It aims to answer frequent questions we have about this material, such as:

1) What value do these tools have without causal inference?

August 25, 2015
Coordinator:
Andy Lyons

A long-standing challenge to the broader adoption of R is its command line interface and the steep learning curve of the syntax. This is where Shiny comes in. Shiny is a package that allows you to create HTML based applications that connect to R running in the background. Shiny apps can be run locally or off the internet, making it far simpler for you to share your work with non-R users.

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