HPC-Launch (September 2024)
![HPC Launch logo HPC Launch logo](/images_new/courses/1100x600_course-images/1100x600_Course_Image_HPC-Launch.png)
A 1-day course to support the launch (and/or reconfiguration) of health data projects from an efficient and modern computing and data management perspective
Targeting trainees and researchers in bioinformatics and large-scale health records, the course will consist of two modules: High-Performance Computing (HPC) and Research Data management (RDM). With the HPC module, we want to expand understanding and efficient use of HPC resources for complex health data science projects. We will fill gaps in technical understanding for beginner to intermediate users of supercomputing platforms and share up-to-date information on computing resources available to Danish researchers and how to get access.
HPC-Launch will provide participants with an overview of current best computing practices for management of health data analysis projects. The two modules are designed to enhance participants’ ability to handle large datasets, conduct sophisticated analyses of biodata, and preserve data and analyses for future projects and project members.
HPC-Launch is the first course of a series we are developing to elevate practical technical skills in health data science, and is the intended prerequisite for HPC-Pipes (focused on environment management and bioinformatics pipeline languages) and/or HPC-ML (focused on set-up and optimization of large-scale machine learning projects on HPC platforms).
Requirements
The workshop is for researchers, professors, and PhD students at SUND who seek to acquire skills in effectively managing data and computing projects.
The course is targeted to students performing data analysis on biological research or within the field of data science, therefore some computational experience is required, and basic knowledge of R/Python and bash is highly recommended for the demo session.
Interested?
➡️ If you are an employee, sign up here
➡️ If you are a PhD student, sign up here
Course Disclaimers:
- The course is free of charge and intended for all KU researchers, and especially PhD students, at SUND
- A no-show free will be implemented for registrants who do not attend the course
- If you are a PhD student and you would like to receive ECTS credits for participating in this course, you must enroll through the PhD school school system
- If you are not a PhD student and sign up via the PhD school registration link, you will be charged for the course
- Please be advised that course participation via the PhD school happens under the PhD school's terms and conditions which HeaDS has no influence over