The most widely used way to interact with computers is through a graphical user interface, for example, the desktop interface of Microsoft Windows or Mac OS. However, you can also use a text interface to interact with your computer (or with a computing system like Hoffman2). This can variously be referred to as the command...
Shell scripts enable users to link together multiple Linux commands into a single executable program. They can save users from a lot of wasted time, effort, and headache. For example, many researchers execute many different steps and run several different programs during their process of transforming raw data into analyzable results and ultimately into polished...
In this workshop the DCP will lead a training on how the design accessible data visualization for publication both into PDF and html in alignment with WCAG 2.1 AA guidance. Many people with disabilities use assistive technologies. Register Now
As artificial intelligence (AI), machine learning (ML), and Large Language Models (LLM) technologies continue to evolve, they offer new possibilities for humanities research, from large-scale text and image analysis to generative AI applications that synthesize and extrapolate knowledge. This workshop introduces key AI/ML/LLM concepts, including neural networks, large language models, and large image models, while...
This workshop will cover running Large Language Models (LLMs) on the Hoffman2 HPC cluster using Ollama for inference and Open WebUI for an easy-to-use interface. Participants will learn how to set up and manage LLM workloads on HPC resources, optimize performance, and interact with models through a web-based UI. The session includes a live demo,...
Are you doing research with surveys ( in RedCap or another survey tool) and paying an outside vendor to SMS links to your participants? Did you know that UCLA has a Mobile Messaging service that can send push messages instead that is much more economial? Sending a push message to a simple mobile app costs...
In this workshop, participants will gain hands-on experience with the job scheduling system on the Hoffman2 cluster, the UCLA’s high-performance computing resource. Additionally, participants will learn how to write effective job submission scripts, allocate resources efficiently, troubleshoot job issues, and optimize workflows for improved performance. Whether you're new to job scheduling or looking to refine...
Machine learning has become a key element in science and technology today. Mastering libraries like scikit-learn–a vital tool for machine learning–is essential. In this workshop, you'll receive a fundamental introduction to the scikit-learn Python library. For the best experience, participants should have a working knowledge of Python and a basic understanding of machine learning concepts....
What is digital accessibility? How can the research enterprise be more prepared to be inclusive of people with disabilities. What should an IRB be evaluating in terms of digital accessibility? Strategic Outcomes: Increased awareness of digital accessibility issues; improved inclusion of disabled populations in UCLA's research studies; positions UCLA researchers to better serve disabled populations...
The analysis of binary outcomes is widespread across scientific fields. This workshop introduces the basics of the most commonly used statistical model for binary outcomes, logistic regression. Some basic background on probability and odds will be provided, as well as a brief review of the model itself. This workshop then covers how to run a...
Machine learning is playing an increasingly important role in science and technology. In this advanced session, we focus on leveraging scikit-learn for high-performance machine learning. We will explore how to speed up model training using multicore processors and accelerators, as well as techniques for out-of-core learning. This workshop builds on the foundational concepts from the...
Are you interested in using LLMs for research? In this 90 minute hands-on workshop, you will learn how to install and deploy an open-source LLM on your local environment, create a Retrieval Augmented Generation (RAG) model with visual builders from Diffy and AWS Bedrock and learn prompt-engineering techniques to reduce the occurrence of hallucination and...
The purpose of this workshop is to show the use of the mixed command in SPSS. Although it has many uses, the mixed command is most commonly used for running linear mixed effects models (i.e., models that have both fixed and random effects). Such models are often called multilevel models. Because the purpose of this...
Learn how to rapidly build a low cost AI prototype for research and education with custom GPTs, prompt engineering, and turn-key solutions from leading LLM providers. Register Now
This workshop provides an introduction to using multiple GPUs for high-performance computing. Participants will explore essential techniques and tools, including CUDA with C++ and Python, PyTorch, and MPI, to optimize performance and handle complex computations. CUDA with C++ and Python will be used to demonstrate the basics of GPU programming, memory management, and multi-GPU computations....
This workshop introduces power analysis and simulations to assess power and estimate sample sizes needed for sufficient power. We will begin with simple analyses such as the t-test and will work our way up to various regression models. We will provide guidance in R to program simple Monte Carlo simulations to assess power. Some background...
This workshop explores designing AI interfaces for research mobile apps, focusing on enhancing user experience. Participants will learn how to leverage Retrieval Augmented Generation (RAG) architectures to achieve accurate performance in specific research domains and specialties. There will be a focus on agentic AI functionality in software products to streamline data collection and ensure compliance...
Directed Acyclic Graphs (DAGs) have emerged as an important tool in causal modeling to understand the relationships among variables. DAGs can inform what variables should be included or excluded in a statistical model intended to minimize bias in the estimation of a causal effect. This workshop discusses the basics of DAGs used for causal inference...