We teach foundational coding and data science skills to researchers worldwide.

A comprehensive list of training resources from the HPC University. HPCU is a virtual organization whose primary goal is to provide a cohesive, persistent, and sustainable on-line environment to share educational and training materials for a continuum of high performance computing environments that span desktop computing capabilities to the highest-end of computing facilities offered by HPC centers.

An HPC focused Carpentry community. Trainings include: HPC fundamentals, python, chapel, LAMMPS, parallelization with python, scaling studies, etc.

Monthly workshops sponsored by ACCESS on a variety of HPC topics organized by Pittsburgh Supercomputing Center (PSC). Each workshop will be telecast to multiple satellite sites and workshop materials are archived.

Cornell Virtual Workshop is a comprehensive training resource for high performance computing topics. The Cornell University Center for Advanced Computing (CAC) is a leader in the development and deployment of Web-based training programs. Our Cornell Virtual Workshop learning platform is designed to enhance the computational science skills of researchers, accelerate the adoption of new and emerging technologies, and broaden the participation of underrepresented groups in science and engineering. Over 350,000 unique visitors have accessed Cornell Virtual Workshop training on programming languages, parallel computing, code improvement, and data analysis. The platform supports learning communities around the world, with code examples from national systems such as Frontera, Stampede2, and Jetstream2.

Self-paced tutorials on high-end computing topics such as parallel computing, multi-core performance, and performance tools. Other related topics include 'Cybersecurity for End Users' and 'Developing Webinar Training.' Some of the tutorials also offer digital badges. Many of these tutorials were previously offered on CI-Tutor. A list of open access training courses are provided below. Parallel Computing on High-Performance Systems Profiling Python Applications Using an HPC Cluster for Scientific Applications Debugging Serial and Parallel Codes Introduction to MPI Introduction to OpenMP Introduction to Visualization Introduction to Performance Tools Multilevel Parallel Programming Introduction to Multi-core Performance Using the Lustre File System

A tutorial on the effective use of Dask on HPC resources. The four-hour tutorial will be split into two sections, with early topics focused on novice Dask users and later topics focused on intermediate usage on HPC and associated best practices. The knowledge areas covered include (but are not limited to): Beginner section High-level collections including dask.array and dask.dataframe Distributed Dask clusters using HPC job schedulers Earth Science data analysis using Dask with Xarray Using the Dask dashboard to understand your computation Intermediate section Optimizing the number of workers and memory allocation Choosing appropriate chunk shapes and sizes for Dask collections Querying resource usage and debugging errors

A series of interviews with women in the HPC community

learning cybersecurity is crucial for personal protection, safeguarding digital assets, financial security, and national security. It is important when it comes to consumer data protection for business, creating long lasting relationships with customers.

Cybersecurity Guide is a comprehensive resource for students and early career professionals that provides users with a wide range of resources and up-to-date information on cybersecurity, including cybersecurity degree programs and bootcamps, career guides, as well as online courses and training opportunities. Additionally, it covers trends, best practices, and much more.

The mission of Trusted CI is to lead in the development of an NSF Cybersecurity Ecosystem with the workforce, knowledge, processes, and cyberinfrastructure that enables trustworthy science and NSF’s vision of a nation that is a global leader in research and innovation.

This is a self guided online course on compilers. The topics covered throughout the course include universal compilers topics like intermediate representations, data flow, and “classic” optimizations as well as more research focusedtopics such as parallelization, just-in-time compilation, and garbage collection.

This workshop has an introduction to the concepts of visualization followed by hands on exercises. The concepts section has Speaker Notes, and the hands on section has an accompanying Jupyter notebook. The workshop is one in a series of Introduction to HPC

CS244N is a renowned natural language processing course offered by Stanford University and taught by Christopher Manning. It covers a wide range of topics in NLP, including language modeling, machine translation, sentiment analysis, and more. It teaches both foundational concepts and cutting-edge research to gain a comprehensive understanding of NLP techniques and applications.

With the recent uprising of LLM's many business are looking at way to adopt these LLMs and fine-tuning these models on specfic data sets to ensure accuracy. These models when fine-tuned can be optimal for fulfilling the specific needs of a company. This site explains explicitly when, how, and why models should be trained. It goes over various strategies for LLM fine -tuning.

Introductory video about DELTA. Speaker Tim Boerner, Senior Assistant Director, NCSA

This webinar series is an orientation to R. We start with an overview of R’s history and place in the larger data science ecosystem. Next, we introduce the R Studio user interface and how to access R’s excellent documentation. Finally, we present the fundamental concepts you need to use the R environment and language for data analysis. Along the way, we compare R script files (.R) to R Notebook (.Rmd) files and show how the features of R Notebook support better communication and encourage more dynamic engagement with statistical analysis and code. It is helpful to be familiar with tabular data analysis using statistical software, database tools, or spreadsheet programs. Workshop materials, including setup directions and slides are available at https://github.com/CornellCAC/r_for_edu/ The Rstudio Cloud project used in the workshop is https://rstudio.cloud/project/4044219.

A class from MITOpenCourseware that gives a hands on approach to building scalable and high-performance software systems. Topics include performance analysis, algorithmic techniques for high performance, instruction-level optimizations, caching optimizations, parallel programming, and building scalable systems.

A library of short videos about ACCESS allocations, resources and support.

Introduction to the Slurm Workload Manager for users and system administrators, plus some material for Slurm programmers.

This is a short video on how to exchange ACCESS credits and connect to Jetstream 2 (please note this was created for Duke users but applies to all) .

The United Nations (UN) is an international organization comprising 193 Member States, including the United States. As a global organization, the UN is the one place on Earth where the world's nations can gather to discuss common problems and find shared solutions that benefit all humanity. This handbook has been produced for UN staff of all backgrounds and levels and provides an overview of how to approach your participation in a mentorship program. This resource is quickly digestible and provides a basic structure that will be helpful to review before the first meeting with your mentee.

Self-paced tutorials on high-end computing topics such as parallel computing, multi-core performance, and performance tools. Some of the tutorials also offer digital badges.

Tableau is a popular and capable software product for creating charts that present data and dashboards that allow you to explore data. It is typically used to present business or statistical data, but can also create compelling visualizations of scientific data. However, scientific data is often generated or stored in formats that are not immediately accessible by Tableau. This seminar will explore the data formats that work best with Tableau and the available mechanisms for generating scientific data in (or converting it to) those formats so that you can apply the full power of Tableau to create the best possible visualizations of your data.