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The University of Amsterdam has many data science resources available for researchers and students.

Open Data at the UvA Library

The University Library strives to make its collections as open as possible, including the data and metadata required to access these, and to make the products of education and research of the institutions of the University of Amsterdam (UvA) and of education and research institutions across the globe as accessible as possible. Providing open access to the collection metadata in various ways and through various channels plays a central role in this regard.

DSC GitHub

The DSC GitHub is a collaborative public workspace where the DSC collaborates on data repositories, code, and other related materials. 

For example, you can find materials from previous DSC activities and workshops on topics such as Dash, Shiny, Deep Learning, Conventional Machine Learning, and Data Visualisation.

The DSC supports open education and is committed to continuously updating the DSC GitHub.


High-Performance Computing

As researcher or engineer you might frequently be impeded in your work by physical limitations of the available ICT equipment: processing and storage capacity, visualization facilities and their integration. Up-scaling to high performance computing (HPC) facilities could be very beneficial to your work.

High-Performance Computing & Big Data Course - June 2021

In this course you will be introduced to various HPC facilities by researchers from the UvA and HPC experts from SURFsara. 

During the course you will learn how to use various HPC facilities. You will have the opportunity to discuss your specific problems with experts and work on solutions using SURFsara's state-of-the-art computing facilities. The course is taught in English. In ten sessions, a number of independent modules touching on various HPC and Big Data issues will be addressed:

  • Introduction to Unix, distributed systems, and Big Data
  • Using state-of-the-art Super Computers (with hands-on on the National Super Computer Cartesius and the Lisa cluster)
  • HPC Cloud
  • GPU programming
  • Local and Remote Visualization Techniques
  • Data management
  • Data Intensive Computing with Hadoop: MapReduce and Pig
  • MPI/OpenMP approaches used in HPC and distributed computing

For more information and to register, please visit the course website. For questions, you may contact Boy Menist.