Software for Data Analysis

All workshops are 2-week asynchronous courses held in Canvas. The total amount of participation time is approximately 3 - 4 hours (Unix, Git, OpenRefine) and approximately 7-8 hours (Python, R). Zoom sessions will be available, along with ways to receive help within Canvas.  Registered participants will receive invites to the Canvas workshop, click on the links above to register.

Please contact Danielle Kane (kaned@uci.edu) if interested:

• in holding workshop(s) for specific groups, departments, and/or labs. 
• in a workshop(s) that we currently do not hold in Software Carpentry, Data Carpentry, and Library Carpentry.

OpenRefine (4 hrs)

OpenRefine is described as “a power tool for working with messy data” David Huynh - but what does this mean? It is probably easiest to describe the kinds of data OpenRefine is good at working with and the sorts of problems it can help you solve.

The Unix Shell (4 hrs)

The Unix shell has been around longer than most of its users have been alive. It has survived so long because it’s a power tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren’t typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources (including “high-performance computing” supercomputers). These lessons will start you on a path towards using these resources effectively.

Version Control with Git (3-4 hrs)

Version control is the lab notebook of the digital world: it’s what professionals use to keep track of what they’ve done and to collaborate with other people. Every large software development project relies on it, and most programmers use it for their small jobs as well. And it isn’t just for software: books, papers, small data sets, and anything that changes over time or needs to be shared can and should be stored in a version control system.

Programming with Python (7 hrs)

Python is a programming language that lets you work more quickly and integrate systems more effectively.  Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages.

Programming with R (6 hrs)

R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis.