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2024 Free Online Course on High-performance Computing for Reproducible Genomics

Harvard University is offering a free online course on High-performance Computing for Reproducible Genomics.

Students will discuss how to create interactive reports that enable us to move beyond static tables and one-off graphics so that our analysis outputs can be transformed and explored in real-time.

In this four-week course, applicants will learn how to bridge from diverse genomic assay and annotation structures to data analysis and research presentations via innovative approaches to computing. This course will start on September 7, 2024.

Table of Contents Hide
  1. Course At A Glance 
  2. Providers’ Details
  3. About This Course
  4. Learning Outcomes for Free Online Course on High-performance Computing for Reproducible Genomics
  5. Instructors
    1. Rafael Irizarry
    2. Vincent Carey
    3. Michael Love
  6. Requirements
  7. How To Join This Course
  8. Recommendations

Course At A Glance 

Length: 4 weeks
Effort: 2-4 hours per week
Subject: Biology & Life Sciences
Institution: Harvard University and Edx
Languages: English
Price: Free
Certificate Available: Yes, Add a Verified Certificate for $49
Session: The course Starts on September 7, 2024

Providers’ Details

Harvard University is devoted to excellence in teaching, learning, and research, and to developing leaders in many disciplines who make a difference globally. 

Harvard faculty are engaged with teaching and research to push the boundaries of human knowledge.

The University has twelve degree-granting Schools in addition to the Radcliffe Institute for Advanced Study.

About This Course

This free online course on High-performance Computing for Reproducible Genomics is explained below.

If you’re interested in data analysis and interpretation, then this is the data science course for you.

Enhanced throughput: Almost all recently manufactured laptops and desktops include multiple core CPUs. With R, it is very easy to obtain faster turnaround times for analyses by distributing tasks among the cores for concurrent execution.

University will discuss how to use Bioconductor to simplify parallel computing for efficient, fault-tolerant, and reproducible high-performance analyses. This will be illustrated with common multicore architectures and Amazon’s EC2 infrastructure.

Enhanced interactivity: New approaches to programming with R and Bioconductor allow researchers to use the web browser as a highly dynamic interface for data interrogation and visualization.

Also, University will discuss how to create interactive reports that enable us to move beyond static tables and one-off graphics so that our analysis outputs can be transformed and explored in real-time.

Enhanced reproducibility: New methods of virtualization of software environments, exemplified by the Docker ecosystem, are useful for achieving reproducible distributed analyses.

The Docker Hub includes a considerable number of container images useful for important Bioconductor-based workflows, and University will illustrate how to use and extend these for sharable and reproducible analysis.

Learning Outcomes for Free Online Course on High-performance Computing for Reproducible Genomics

  • Parallel Computing
  • Interactive Graphics
  • Reproducible distributed analysis

Instructors

Rafael Irizarry

Rafael Irizarry is a Professor of Biostatistics at the Harvard T.H. Chan School of Public Health and a Professor of Biostatistics and Computational Biology at the Dana Farber Cancer Institute.

Vincent Carey

Vincent Carey is Associate Professor of Medicine (Biostatistics) in the Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School.

Michael Love

Michael Love is a postdoctoral fellow with Dr. Irizarry in the Department of Biostatistics at the Dana Farber Cancer Institute and Harvard T.H. Chan School of Public Health.

Requirements

PH525.3x, PH525.4x

How To Join This Course

  • Go to the course website link
  • Create an edX account to Sign up
  • Choose “Register Now” to get started.
  • edX offers honor code certificates of achievement, verified certificates of achievement, and XSeries certificates of achievement. Currently, verified certificates are only available in some courses.
  • Once applicants sign up for a course and activate their account, click on the login button on the edx.org homepage and type in their email address and edX password. This will take them to the dashboard, with access to each of their active courses. (Before a course begins, it will be listed on their dashboard but will not yet have a “view course” option.)
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Application Link

Recommendations

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