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February 2023
Automation with Make and Makefiles
Make is a tool that can be used to automate the process of building programs, libraries, plots, and even papers. Make keeps track of the dependencies between files during this process, and if any file changes, Make knows how to update the built object to account for the updates. This can be a valuable tool for software development, where source code files can be frequently updated and recompiled into programs and libraries, and it can also be valuable more generally…
Find out more »Cornerstone 5: Writing a Literature Review Workshop
Writing a literature review can seem like a daunting task. Attend this interactive workshop to learn strategies for writing a literature review! This workshop is free and open to all undergraduates. This workshop is offered as part of the Cornerstone Research Workshops, a six-part series covering foundational research topics and skills created by URC-HASS, the UCLA Library, and the Undergraduate Writing Center. Join meeting here: https://bit.ly/urcworkshop
Find out more »Version Control with Git and GitHub
Git is a software tool that helps users manage changes to their software over time, and GitHub is a web-based platform for using Git and version control. They will allow you to maintain a complete change history of your files, create branches for concurrent streams of changes, trace changes with annotations, and collaborate and share work with others. This interactive introduction will demonstrate how to use Git and GitHub to track changes, explore history, and use web-based Git repositories to…
Find out more »Cornerstone 6: Developing a Research Plan
Streamline your research plan and learn how to organize your drafts, resources, and time when writing a research assignment. This workshop is free and open to all undergraduates. This workshop is offered as part of the Cornerstone Research Workshops, a six-part series covering foundational research topics and skills created by URC-HASS, the UCLA Library, and the Undergraduate Writing Center. Join meeting here: https://bit.ly/urcworkshop
Find out more »Learning Convolutional Neural Networks (1)
This workshop will provide an introduction to convolutional neural networks (CNNs). We will begin by using PyTorch to perform image processing on the classic Dogs-vs-Cats problem. Basic knowledge of the topics covered in previous sessions is assumed. Having working experience with Python, Jupyter Notebooks, and linear algebra will be helpful for fully participating in the workshop. Any questions about this workshop can be emailed to Qiyang Hu at huqy@oarc.ucla.edu. Presented by the Office of Advanced Research Computing (OARC). Register here: https://ucla.zoom.us/meeting/register/tJwqdO6gqzMqE9Tow2G8OoEaPtGrPoDXypK4
Find out more »Code Profilers: Measuring Performance and Resource Usage
Learn to use code profilers (software) to analyze a program's performance and resource usage, and to use the measurement data to guide tuning methodologies and workflows, in the context of scientific computing. Any questions about this workshop can be emailed to Shao-Ching Huang at sch@ucla.edu. Presented by the Office of Advanced Research Computing (OARC). Register here: https://ucla.zoom.us/meeting/register/tJIodumoqD0tG9cM27ylElmFbQzauFoBLpRL
Find out more »Learning Convolutional Neural Networks (2)
This workshop will be the second lecture in our introduction to convolutional neural networks (CNNs). We will continue our learning by applying data augmentation and transfer learning techniques to improve our solution for the classic Dogs-vs-Cats problem using PyTorch. A basic understanding of the topics covered in previous sessions is assumed. Having working experience with Python, Jupyter Notebooks, and linear algebra will be helpful for fully participating in the workshop. Any questions about this workshop can be emailed to Qiyang Hu at huqy@oarc.ucla.edu.…
Find out more »Introduction to Meta-analysis in Stata
Meta-analysis is the synthesis of results from previous studies. It is used to increase power, obtain a better estimate of an effect size, and sometimes to resolve conflicting conclusions in the literature. In this workshop, we will discuss how the data for a meta-analysis are collected and organized, as well as how such data are analyzed and graphed. We will also discuss some of the limitations meta-analysis and what should be included in a meta-analysis for publication. Any questions about…
Find out more »March 2023
Research and Creative Proposal Workshop
Learn how to write a research or creative proposal for scholarship program applications! Applications for the Undergraduate Research Fellows Program (URFP) and the Mellon Mays Undergraduate Fellowship (MMUF) are due by November 15. Join meeting here: https://bit.ly/urcworkshop
Find out more »Learning Generative Adversarial Networks
This workshop will introduce participants to Generative Adversarial Networks (GANs). We will demonstrate the core techniques of GANs, including how to use Deep Convolutional GANs (DCGANs) to generate images using PyTorch. A basic understanding of the topics covered in previous sessions is assumed. Having working experience with Python, Jupyter Notebooks, and linear algebra will be helpful for fully participating in the workshop. Any questions about this workshop can be emailed to Qiyang Hu at huqy@oarc.ucla.edu. Presented by the Office of Advanced Research Computing…
Find out more »Missing Data in R
The purpose of this seminar is to discuss techniques and introduce some useful packages in R for handling missing data. In particular, we will focus on multiple imputation and how to perform it using the R package, mice: “Multivariate Imputation by Chained Equations”. As prerequisite to this seminar, we suggest participants have basic knowledge in R and if they do not have prior training in R, a seminar providing an introduction R can be found here: https://stats.idre.ucla.edu/r/seminars/intro/. Any questions about…
Find out more »Decomposing and Visualizing Interactions in R
In regression, we are often interested in an interaction, which is the modification or moderation of the effect of an independent variable by another. Understanding interactions involves interpreting the regression coefficients, estimating and testing simple effects and their differences, and visualizing the interaction. This workshop will teach you how to do all of these thing in R using base R, as well as the emmeans and ggplot2 packages. Some prior knowledge of linear regression and experience with R is recommended…
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