ARC runs a series of training courses to introduce researchers and other members of staff to High Performance Computing (HPC). The courses are run termly, are open to all University staff and students and are free of charge.
The benefits of the courses include:
- a quick introduction to the ARC computing facilities,
- practical experience with using the ARC systems
- an introduction to how to best exploit modern computational facilities
The courses are hands-on and trainees have plenty of opportunity to ask questions from ARC members of staff and gain practical experience. Full copies of the course notes and exercises are provided.
Course Dates and Registration
Full details of the courses and how to register for them is available through the course booking system at courses.it.ox.ac.uk (search for High Performance Computing). Note not all courses will be run each term; if you have particular interest in a specific course please get in touch either via the courses catalogue or the helpdesk and we will do our best to schedule it.
Prerequisites for individual training courses are available on the registration site.
Trainees are requested to bring their own laptops to use during the hands-on elements of these courses.
In order to connect to the University network, trainees may need to use the VPN service. An alternative is to use the IT Services server linux.ox.ac.uk; to activate an account on it a user first needs to go to https://register.it.ox.ac.uk/self/index and select 'Manage Linux Shell Account' situated towards the bottom of the page.
For the hands on sessions, the FAQ entries on how to log in to the ARC systems and on how to transfer filescould also be useful. Also an Introduction to Linux guide is recommended reading before attending Course 1:
The following course material is available for past training.
- ARC: Statistical learning for data science - basic techniques using R
- ARC: Statistical learning for data science - advanced techniques using R
- ARC: Statistical learning for data science - data wrangling with R