Research Computing

Becker Library offers free trainings to the Washington University Medical Center community on a variety of research computing topics, including:

  • Computing 101
  • MATLAB
  • Python
  • R

These workshops are meant to serve as an introduction to research computing basics and prepare participants for ongoing learning. Check below to see what’s coming up or sign up for the mailing list to be notified each time a new workshop is scheduled.

Sign up for the mailing list

Contact Maze Ndukum (ndukummaze@wustl.edu) or Marcy Vana (vanam@wustl.edu) with any questions.

Upcoming Workshops

These workshops are designed for those without prior experience in Python and programming.  Each workshop session will occur from 10AM – 11AM on the two dates below. Registration is required to receive a Zoom link. Click on a date below to learn more and register for one or both sessions.

Using Python for Basic Data Exploration and Manipulation – 7/27/2021

This workshop will introduce the Python programming language and demonstrate import, exploration & manipulation of a practice dataframe dataset using the Pandas Library.

Using Python for Basic Data Visualization – 8/3/2021

This workshop will introduce basic data visualization using Python. Attendees will learn how to create simple Python plots using the Matplotlib, Seaborn, and Plotly Express libraries.

View a comprehensive list of Library classes and workshops

Previous Workshops

These workshops were offered in collaboration with the Center for High Performance Computing (CHPC) and were geared toward researchers new to high performance computing and the command line interface. During each workshop session, important background concepts related to computing were introduced in a simple presentation format, followed by hands-on exercises. While these workshops were focused on using the CHPC, the knowledge gained could be applied to other computing environments. The materials from these workshops can be found here.

#1 Tools to Connect and Move Data & Getting Around the Linux Command Line Interface – 3/26/19

Goals: to develop a basic understanding of the tools needed to connect to the CHPC and transfer data back and forth, and become familiar with the Unix file system and basic Unix commands

#2 Text Editors and Shell Scripts – 4/2/19

Goals: to gain knowledge of some of the options for text editors and learn how to write and execute basic shell scripts

#3 Running Jobs on the CHPC Cluster – 4/9/19

Goal: to learn how to write and submit batch scripts to run applications on the CHPC cluster

These MATLAB webinars were organized in collaboration with WUIT’s Research Infrastructure Services (RIS), and were led by MathWorks Engineers. See below for a description of each workshop and links to the workshop materials.

 Parallel Computing with MATLAB – 3/25/2021 at 10AM

Using the Parallel Computing capabilities in MATLAB allows users to take advantage of additional hardware resources that may be available either locally on their desktop or on clusters, clouds, and grids. By using more hardware, you can reduce the cycle time for your workflow and solve computationally and data-intensive problems faster.  This webinar, discussed a range of workflows available to scale MATLAB applications with minimal changes to your MATLAB code and without needing to learn low-level programming. Below are some of the highlights discussed:

  • Leveraging multiple cores or CPUs
  • Working with high-level constructs—parallel for-loops, special array types, and parallelized numerical algorithms.
  • Scaling up to utilize clusters, grids and clouds
  • Utilizing tall and distributed arrays to work with large data sets
  • Using MATLAB for GPU computing

 NOTE: MATLAB is accessible on WUIT’s RIS compute cluster. You can request access to RIS compute and storage to leverage MATLAB, to do so, use your WUSTL key to log in here (All WashU Faculty have access to 5TB of free storage available to them). Please visit the RIS website to learn more.

Workshop recording and other materials are located here.

Image Processing Made Easy Using MATLAB – 3/25/2021 at 1PM

Image processing is the foundation for building vision-based systems based on cameras and frame grabbers. You might have a new idea for using your camera in the fields of engineering, sciences, biomedical, or oceanography, for example, and are not sure where to start. This webinar focussed on several key workflows to make things easy and help get you started. The real-world examples presented were focused on:

  • Pre-processing images using enhancement and filtering techniques
  • Separating objects of interest using segmentation techniques
  • Testing your algorithm on large sets of images

Some highlights discussed during the webinar include:

  • MATLAB help documentation and examples help with getting started quickly
  • Interactive apps and live scripts enable exploration of different techniques
  • Extensive library of built-in image processing algorithms

Workshop recording and other materials are located here.

These MATLAB training sessions were organized in collaboration with the Center for High Performance Computing (CHPC) and were led by MathWorks Engineers. See below for a description of each workshop and links to the workshop materials.

Demystifying Deep Learning: A Practical Approach in MATLAB – 5/14/2019

This seminar discussed MATLAB features that make it easy to:

  • Manage extremely large sets of images
  • Visualize networks and gain insight into the black box nature of deep networks
  • Perform classification and pixel-level semantic segmentation on images
  • Import training data sets from networks such as GoogLeNet and ResNet
  • Import and use pre-trained models from TensorFlow and Caffe
  • Speed up network training with parallel computing on a cluster
  • Automate manual effort required to label ground truth
  • Automatically convert a model to CUDA to run on GPUs

Workshop slides and other materials can be found here.

Parallel and GPU Computing with MATLAB – 5/14/2019

This hands-on workshop was focused on using MATLAB on the CHPC cluster. The following topics were discussed:

  • Toolboxes with built-in algorithms for parallel computing
  • Creating parallel applications to speed up independent tasks
  • Scaling up to computer clusters, grid environments or clouds
  • Employing GPUs to speed up your computations

Workshop slides and hands-on exercises can be found here.

Image Processing for Medical Applications Using MATLAB – 5/3/2018

This MATLAB training seminar included the following topics:

  • Analyzing medical images using MATLAB Apps
  • Image thresholding
  • Finding ROI properties
  • Automating your workflow with MATLAB

Workshop slides and other materials can be found here.

Using Python for Basic Data Visualization – March 2021

This workshop introduced three popular libraries used for data visualization in Python. Attendees learned how to create and customize simple Python plots using the Matplotlib, Seaborn, and Plotly Express libraries. Workshop materials and a recording of the workshop can be found here.

Using Python for Basic Data Exploration and Manipulation – February 2021

This workshop introduced the Python programming language. A practice dataset was used to demonstrate import, exploration & manipulation of data from a dataframe using the Pandas library. Workshop materials and a recording of the workshop can be found here.

Basic Data Analysis Using Python – February 2021

This Love Data Week workshop introduced popular libraries for data analysis in Python and demonstrated common data analysis tasks including data  import, exploration & manipulation using the Pandas library as well as data visualization using the Matplotlib, Seaborn, and Plotly Express libraries. The hands-on exercises were presented in Jupyter Notebook. All the workshop materials can be found here.

R vs. Python – Love Them Both? – October 2020

This workshop was offered by WashU’s Institute for Informatics, University Libraries and Becker Medical Library on Zoom. The workshop introduced some common data analysis tasks in the R and Python programming languages and explored which language is better suited for a particular task. During the hands-on portion of the workshop, basic Python and R code were explained using the interactive web-based environments, repl.it and RStudio Cloud respectively. The workshop materials are located here.

Introduction to Python – September and October 2019

These Introduction to Python workshops were offered in collaboration with the Center for High Performance Computing and Institute for Informatics and were geared toward researchers new to programming and Python. Each workshop started with a 30-minute presentation covering important background information and then the remaining 90 minutes was devoted to hands-on activities.

Introduction to Python #1 – Getting Started with Python – 9/25/19 and 9/26/19

Goals: to develop a basic understanding of the Python programming language and to run basic Python code in the interactive Python environment, Jupyter Notebook

Previous workshop slides and hands-on activities

Introduction to Python #2 – Using Python for Data Analysis – 10/2/19 and 10/3/19

Goals: to learn to write Python code to perform data analysis and visualization, and create a Python virtual environment on a remote system

Previous workshop slides, hands-on activities, and data (weather_data_newyork, snow_data)

Visualization of COVID-19 Data Using R – February 2021

This Love Data Week workshop provided an introduction to using R packages for visualization of COVID-19 data. Participants learned about the structure of publicly available COVID-19 data and explored methods to visualize the data with an aim to understand the disease epidemiology. The R code for this session can be found in this RStudio Cloud Project. All workshop materials are located here.

R vs. Python – Love Them Both? – October 2020

This workshop was offered by WashU’s Institute for Informatics, University Libraries and Becker Medical Library on Zoom. The workshop introduced some common data analysis tasks in the R and Python programming languages and explored which language is better suited for a particular task. During the hands-on portion of the workshop, basic Python and R code were explained using the interactive web-based environments, repl.it and RStudio Cloud respectively. The workshop materials are located here.

Genomic Data Analysis Using Bioconductor – October 2020

This workshop was offered by WashU’s Institute for Informatics, University Libraries and Becker Medical Library on Zoom. This virtual workshop provided an introduction to using R and Bioconductor for computational genomics. EdgeR and ShortRead packages were used to perform RNA sequencing data analysis, introducing various data formats, data input and output, data analysis and visualization. During the hands-on activities, R code was explained using the interactive web-based environment, RStudio Cloud. The workshop materials are located here.

Introduction to R Zoom Workshops – September 2020

These virtual workshops were geared toward researchers new to programming and R. During each session important background concepts were introduced in a simple presentation format, followed by hands-on exercises. The workshop materials can be found here.

Introduction to R

This workshop introduced R data objects and functions, basic data exploration, manipulation, and visualization, all using R base.

Introduction R – Data Visualization in R Using ggplot2

This workshop introduced R packages and covered installing, loading and managing R packages as well as basic data visualization using the ggplot2 package.

Introduction to R – Bioconductor

This workshop introduced Bioconductor and covered installing, loading and managing Bioconductor packages as well as basic genomic data exploration with the VariantAnnotation package.