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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. |
Registrations are now managed through the Harvard Training Portal, which requires a Harvard ID (HUID). Those members of the extensive HMS community who do not currently 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. This form may take several days to process, and is available here:
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Spring 2021 (Part 3) Registration is open!
Medical Image Processing and Deep Learning with MATLAB |
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MATLAB helps you gain insight into your image and video data, develop algorithms, and automate image analysis tasks. With just a few lines of MATLAB code, you can apply deep learning techniques and build deep learning models without having to be an expert. |
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Join us for a complimentary 3-part webinar series and learn how to:
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Session 1: Medical Image Processing with MATLAB (May 13, 2021) Session 2: Pixels to Models: Taking Medical Imaging to the Next Level (May 20, 2021) Session 3: Deep Learning in Medical Imaging (May 27, 2021) |
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To learn more about each session and register visit: https://www.mathworks.com/company/events/seminars/medical-image-processing-and-deep-learning-with-matlab.html |
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R/Biostatistics description:
The HMS Research Computing R Biostatistics course is a three-class, advanced instructional course covering the basics of RNA-seq analysis with Bioconductor and the R statistical programming language. Bioconductor provides tools for the analysis and comprehension of all types of high-throughput genomic data. Students should have a beginner's level of proficiency in R programming and an understanding of basic statistical principles before registering for the course.
The course covers standard supervised statistical approaches for the comprehensive analysis of a published Cancer Genome Atlas (TCGA) human breast cancer RNA-seq dataset. Topics include edgeR differential gene expression analysis and GOSeq functional enrichment analysis of gene ontology terms. Data visualization techniques are emphasized, and each two-hour class includes a lecture and R practicum. The third two-hour class includes a lecture on deep learning in the biomedical sciences. Course registration includes all 3 classes.
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R - https://cran.r-project.org/
RStudio - https://rstudio.com/products/rstudio/download/#download
Spring 2021 (Part 1) Registration is open!
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Class | Date | Time | Location | Seats | Training Materials | Registration (Only click here to register!) |
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Intro to O2 | Wednesday, February 3, 2021 | 3-5pm | Virtual | 30 | ||
Intro to Python | Wednesday, February 10, 2021 | 3-5pm | Virtual | 30 | ||
No class | Wednesday, February 17, 2021 | |||||
Intro to Matlab | Wednesday, February 24, 2021 | 3-5pm | Virtual | 50 | ||
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Intro to Git + Github | Wednesday, March 10, 2021 | 3-5pm | Virtual | 30 | ||
No class | Wednesday, March 17, 2021 | |||||
Intermediate O2 | Wednesday, March 24, 2021 | 3-5pm | Virtual | 30 | ||
Intro to Python | Wednesday, March 31, 2021 | 3-5pm | Virtual | 30 | ||
Intro to Parallel Computing | Wednesday, April 7, 2021 | 3-5pm | Virtual | 50 | ||
Intro to R | Wednesday, April 14, 2021 | 3-5pm | Virtual | 30 | ||
Intro to O2 | Wednesday, April 21, 2021 | 3-5pm | Virtual | 30 | ||
No class | Wednesday, April 28, 2021 | |||||
No class | Wednesday, May 5, 2021 | |||||
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Intro to R | Wednesday, May 26, 2021 | 3-5pm | Virtual | 30 | ||
Intro to O2 | Wednesday, June 2, 2021 | 3-5pm | Virtual | 30 | ||
Introduction to Globus Data Transfer and Data Collaboration on O2 | Wednesday, June 9, 2021 | 3-5pm | Virtual | 30 |
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.
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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.
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.
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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.
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