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Training Update: March 16, 2020

As part of Harvard Medical School's response to COVID-19, HMS Research Computing is now working remotely.

All training classes will be held online until further notice, via Zoom meetings.

Fall 2020 (Part 1) Registration is open!

You must have a Harvard University ID (HUID) to be able to register for a class. This is required to access the Harvard Training Portal.


Those members of the HMS community who do not have HUIDs - such as employees at affiliate hospitals, or collaborators from other institutions - may self-register for one as a "Person of Interest" with their faculty member's sponsorship.  The form may take several days to process, so we encourage non-HUID users to fill out this form ASAP in preparation for upcoming training:  
(please read through the form for submission details)



ClassDateTimeLocationSeatsTraining MaterialsRegistration (Single click directly registers the class)
Intro to O2Wednesday, September 16, 20203-5pVirtual30User Training githublink
Intro to PythonWednesday, September 23, 20203-5pVirtual30User Training githublink
No classWednesday, September 30, 2020




Intro to R/BioconductorWednesday, October 7, 20203-5pVirtual30User Training githublink
Intro to Matlab Wednesday, October 14, 20203-5pVirtual50User Training githublink
Intermediate O2Wednesday, October 21, 20203-5pVirtual30User Training githublink
Intro to O2Wednesday, October 28, 20203-5pVirtual30User Training githublink
Intro to Git/GithubWednesday, November 4, 20203-5pVirtual30User Training githublink
Intro to Parallel ComputingThursday, November 12, 20203-5pVirtual50User Training githublink
Intro to Python Wednesday, November 18, 20203-5pVirtual30User Training githublink
Intro to O2Wednesday, November 25, 20203-5pVirtual30User Training githublink
Intro to PythonWednesday, December 2, 20203-5pVirtual30User Training githublink
Intro to R/BioconductorWednesday, December 9, 20203-5pVirtual30User Training githublink


Intro to O2

O2 for New Users addresses the needs of users who have very little linux experience, and are just getting started with HPC. More time will be devoted to covering linux basics, and the concepts of schedulers and jobs, and data management best practices. The lecture portion of this class is one hour, the second hour will be spent clinic-style with HMS RC staff to address workflow-specific questions and help convert commands to O2 SLURM syntax.

Intro to Python

Python is a popular scripting language for scientific computing and available across all computer platforms. The course will introduce you to some of the basics of the Python language as well as some of the nuances involved with its use specific to the O2 environment. The goal is to provide users with a foundational level of familiarity. Topics covered include basic data types and declaration, flow control (if/else), loops, a brief introduction to constructing a script, and a briefer introduction to modules. The course will be taught on O2, but general concepts are easily translatable to desktop and local installations.

Intro to R/Bioconductor

Intro to using R and Bioconductor. R is a powerful, open-source, highly adaptable statistical language useful for crunching numbers to datasets like those produced by next-gen sequencing. This class covers R basics and learning to think like/understand R. Users will learn how to set up personal R libraries on O2, and use O2 R for its high memory allocations and parallelization. Topics include how to install packages, learn about variables, data types. data manipulation, flow control, and functions, perform simple statistical tests, and create a variety of plots. Laptops are encouraged.

Class Files Here

Intro to MATLAB

Matlab has become the “language of science” in the past few decades. It is simple to use, yet powerful enough to be productive on large computing infrastructures. If you need: 1) Fast prototyping of research ideas; or 2) avoid spending too much time in coding instead of doing real science by taking advantage of Matlab’s built-in functions; 3) User friendly graphical interface and educational documentation; 4) Simplicity of code; 5) Easy access to GPU computing power; 6) Easy plotting and presentation of data; you will find this introduction course useful. This course will introduce the basics of the MATLAB coding language with O2-scalability and data presentation.

Intro to Parallel Computing

This is a short introduction to Parallel Computing that will include an overview of the basic concepts of parallel programming: from running your job in an embarrassingly parallel way to writing simple shared and distributed memory parallelization codes in different languages. The seminar will cover several examples of actual parallel codes however it will not have any "hands on" components. A basic programming experience (of any language, no parallelization) is preferred in order to better follow the topics presented during the seminar.

Intermediate O2

Intermediate O2 is for current O2 users who would like to brush up on their bash skills, learn more advanced file transfer techniques, and unleash some of the powerful features of the SLURM scheduler.

Intro to Git and GitHub

This course introduces Git and GitHub and covers topics including: Getting Started with Git for version control, Using GitHub Desktop effectively, Collaborating with others on GitHub, and Utilizing GitHub Flow for better workflow. No previous exposure is assumed. We hope attendees will leave the class with the knowledge and tools necessary to start integrating Git into their workflows and excited to begin collaborating on GitHub.

Summer 2020 Part2 Registrations are open!


We invite you to attend the following free MATLAB webinars to develop your technical problem-solving skills and make better science.

MATLAB® helps you obtain deeper scientific and clinical insights by giving you the ability to analyze ever increasing amounts of data.  As a platform, MATLAB is flexible and customizable, enabling you to include your own unique workflows and analytics, and allowing you to integrate with other tools. It scales to deal with large data or to combine different modalities and types of data.  As a result, MATLAB has become a platform of choice for researchers.


DateEvent Topic
July 14thData Analysis and Visualization with MATLABRegister
July 21st Optimizing and Accelerating Your MATLAB CodeRegister
July 28thParallel Computing with MATLABRegister
August 4thMATLAB for Medical Imaging Applications Register
August 11thUsing MATLAB with PythonRegister
August 18thText Analytics and Machine Learning with MATLABRegister
August 25thData Science using MATLABRegister
September 1stBig Data: Scale Up to the Cloud with MATLABRegister
September 8thMachine Learning with MATLABRegister
September 15thAutomated Image Labeling and Iterative LearningRegister
September 22ndDeep Learning for NeuroscienceRegister


Additional computational trainings are available through other groups:


Please reach out directly to the above groups if you are interested in attending their trainings.


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