Events

Advanced Research Computing on the Great Lakes Cluster

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OVERVIEW This workshop will cover some more advanced topics in computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and basic use of Great Lakes; dependent and array scheduling; workflow scripting using bash; high-throughput computing using launcher; parallel processing in one or more of Python, […]

Machine Learning on Great Lakes

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OVERVIEW This workshop will go over methods and best practices for running machine learning applications on Great Lakes. We will briefly outline machine learning before stepping through a hands-on example problem to load a project and submit a job to the HPC cluster. Participants are expected to be familiar with Python, the command line, and […]

Reading and discussion group: Spatial Analysis in Social Sciences

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This reading group moderated by consultants from CSCAR will focus on spatial analysis especially as practiced in social sciences. We will meet for 1.5 to 2 hours every month on the fourth Thursday and discuss one or two chapters from relevant graduate level textbooks. We will focus on the concepts and applications but will also […]

Software Development For Research: Git for Collaborative Development

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This is a continuation of the previous workshop "Software Development For Research: Version Control Principles". Now, having learned the basics of version control, we will see how to use the distributed features of Git to publish your project, interact with your collaborators, and incorporate changes from volunteer contributors; for this, we will utilize GitHub, the […]

Software Development For Research: Team-Based Programming Management

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Software development and computer programming is increasingly a major part of scientific research. When small or large teams are involved in coding the same project, it’s a good idea to adopt team-based practices, such as “pair programming” or “code review” meetings, to ensure quality is maintained in the code. This hands-on workshop will provide examples […]

Data Scraping With The Twitter Decahose At The University of Michigan

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Social media platforms are a rich source for data. The University of Michigan collects data with the Twitter Decahose, maintaining an archive of 10% of tweets made from the past decade. This collection is maintained in collaboration by MIDAS, CSCAR and ARC. This workshop covers what the Twitter Decahose is, the process to obtain access, […]

A Beginner’s Guide To Web Scraping With Python

There's a ton of data on the web! You can collect it by using "web scraping!" But what is web scraping? And how do you do it? This workshop is a beginner's guide to web scraping and how to get started using Python and the BeautifulSoup library. Attendees will leave with a better understanding of […]

Introduction to Julia for Statisticians and Data Scientists – Day 1

Rackham Building, Earl Lewis Room, 3rd Floor East 915 E. Washington St., Ann Arbor, MI, United States

This three-part workshop will give an overview of the Julia language for conducting data analyses and managing data. The workshop assumes no prior experience with Julia, but participants should have prior programming experience with a language such as Python, R, or Matlab. The format of the workshop is lecture/discussion but participants may bring a laptop […]

Introduction to Julia for Statisticians and Data Scientists Day #2

Rackham Building, Earl Lewis Room, 3rd Floor East 915 E. Washington St., Ann Arbor, MI, United States

This three-part workshop will give an overview of the Julia language for conducting data analyses and managing data. The workshop assumes no prior experience with Julia, but participants should have prior programming experience with a language such as Python, R, or Matlab. The format of the workshop is lecture/discussion but participants may bring a laptop […]

Introduction to Julia for Statisticians and Data Scientists Day #3

Rackham Building, Earl Lewis Room, 3rd Floor East 915 E. Washington St., Ann Arbor, MI, United States

This three-part workshop will give an overview of the Julia language for conducting data analyses and managing data. The workshop assumes no prior experience with Julia, but participants should have prior programming experience with a language such as Python, R, or Matlab. The format of the workshop is lecture/discussion but participants may bring a laptop […]