Data Essentials summer 2018 workshops

student points to a data visualization on a tv screen

 

Get hands-on experience with a variety of analytic software and be prepared to work with data at different stages of your research, through a series of mini-workshops led by library experts. Topics covered include Open Text Coding, NVIVO, Data Management and Curation, Tableau, Gephi, and Adobe Illustrator. Full-workshop participants have guaranteed seats and lunch provided May 30. Remaining seats for individual session assigned on a first-come, first-served basis as available by registering here.

 

The first, Data Essentials: Tools and Techniques for Organizing, Analyzing and Visualizing Data, will take place May 29-30. Participants in this session will learn how to use a variety of analytic software and work with data at different stages of your research, through a series of mini-workshops led by library experts. Topics include Open Text Coding, Coding and Analysis with NVIVO, Data Management and Curation, Data Visualization with Tableau, Network Visualization with Gephi, and Data Visualization and Information Design with Adobe Illustrator.

 

You can register for the full workshop through the NLI (guaranteed seat) or get on the request list for individual modules (based on availability) at this form. Sign up soon, as we have had strong interest and seats are filling fast.

 

The second option, Software Carpentry, will be all day, August 14-15, with registration through NLI. Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and apply what they have learned to their own research problems. Included sessions will be finalized soon, but it will include a combination of Command Shell (Unix/Bash), Version Control (Git), and Data Analysis (R/Python).