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CoderSpaces Speaker Series

Join our weekly talks in November 2021

Come join the CoderSpaces hosts during the month of November as we share our expertise! Our presenting hosts are a team of ITS Advanced Research Computing (ARC) and Consulting for Statistics, Computing & Analytics Research (CSCAR) consultants, faculty and post-docs, as well as research support staff originating from different research cores at the university.

In this short speaker series, we will introduce you to some of our favorite programming tools, tell you about the resources we support at the university, and showcase the types of work we do. The talks cover advanced research computing, reproducible research practices, workflows, data pipelines, and machine learning applications. Each talk will be about 30 minutes in length followed by a chance to chat with the speaker and learn more. Check out the line up below.

CoderSpaces are weekly virtual research support sessions designed to assist faculty, staff, and students with research methodology, statistics, data science applications, and computational programming. Our hosts have a wide set of methodological and technological expertise. They come to you from a variety of departments and disciplines and are looking forward to serving the U-M community in their research endeavors. CoderSpaces provide a casual, productive and inclusive environment. Everyone is welcome regardless of skill level.

Talk Schedule

*To view the slides, notebooks and recordings, participants need to authenticate with their account.

Wednesday, November 3, 1:30-2pm

Intro to Snakemake: A tool that helps automate complex data workflows/pipelines [slides*] [recording*]

Chris Gates, Managing Director, Bioinformatics Core

Thursday, November 4, 2-2:30pm

Nextflow LIVE! A demo of the Nextflow workflow engine. Or how I learned to love (and not think about) HPC manager [recording*]

Jonathan Golob, Assistant Professor of Internal Medicine, Division of Infectious Diseases

Tuesday, November 9, 2-2:30pm

Sentiment Analysis in Python for Survey Free-Text Responses [slides*][notebook*][recording*]

Liz Hanley, Consulting Statistician and Data Scientist, Population Dynamics and Health Program

Wednesday, November 10, 1:30-2pm

Reproducible data science: Strategies to make your work auditable, scalable and reproducible [slides*][recording*]

Jule Krüger, Program Manager, Center for Political Studies

Thursday, November 11, 2-2:30pm

Using pre-installed software on Great Lakes: Overview of installed software, modules, basic use, creating modules for your own software [slides*] [handout*] [recording*]

Bennet Fauber, Scientific Applications Analyst, and Shelly Johnson, Research Application Specialist, Advanced Research Computing

Tuesday, November 16, 2-2:30pm

Advanced Research Computing 101: Making sense of high performance computing [slides*][recording*]

Alexander Gaenko, Consultant, CSCAR

Wednesday, November 17, 1:30-2pm

Categorizing unstructured text: How you can use spaCy NER in Python to detect custom entity types [slides*] [recording*]

Sara Lafia, Research Fellow, ICPSR

Thursday, November 18, 9:30-10am

As-much-as-we-can-automate: Establishing data pipelines that follow data from electronic capture to analysis [slides*] [recording of a previous talk]

Jon Reader, Data Systems Manager, Michigan Alzheimer’s Disease Center

Thursday, November 18, 2-2:30pm

The Twitter Decahose: How you can access and use U-M’s 10% Twitter sample [recording*][slides*]

Andrew Hlynka, Consultant, CSCAR