NCI and Intersect ran a series of training courses throughout November and December 2021. These courses are aimed at users who may be new to NCI's high-performance computing environment, as well as experienced users looking for a refresher. These course were extremely popular in 2021.
We are opening more spots this year with additional training topics in Machine Learning. Note this series of courses is only offered to NCI users, so please make sure you
r get your NCI account ready when registering for the course.
The following courses are scheduled for the following three months. Please register your interest via this EOI link. We will get in touch with specific dates and a registration link to people who have expressed interest once the course schedule is finalised.
If you registered for a session but can no longer attend, please notify email@example.com so that your place can be allocated to the next person on the waiting list.
|Unix Shell and Command Line Basics|
Use of the shell is fundamental to to a wide range of advanced computing tasks, including high-performance computing. This lesson guides you through the basics of file systems and the shell.
|If you have stored files on a computer at all and recognize the word “file” and either “directory” or “folder” (two common words for the same thing), you’re ready for this lesson.||6h|
|Getting started with HPC using PBS Pro|
This course introduces learners to the core principles behind using a HPC cluster. By the end of this workshop, attendees will know how to login in HPC, use command line to create job scripts, submit and manage jobs using a scheduler, transfer files, use software modules, and basic parallelisation concepts.
This course assumes basic familiarity using the Unix shell. You should be able to use the Unix shell to change directories, read and create files and folders, run programs, and create simple shell scripts.
|Learn to Program: Python||The best way to learn how to program is to do something useful, so this introduction to Python is built around a common scientific task: data analysis.||This lesson sometimes references Jupyter Notebook.||6h|
|Learn to Program: R|
This introduction to R is built around a common scientific task: data analysis.
|We will use RStudio to teach this lesson, but it is not required.||6h|
|Learn to Program: Julia||Julia is a high-level, high-performance dynamic programming language developed in 2012. There is also IJulia, a collaboration between Jupyter and Julia communities, which provides a powerful browser-based graphical notebook interface to Julia.||This course does not require any prior knowledge in programming.||6h|
|Data Manipulation and Visualisation in Python||6h|
|Data Manipulation and Visualisation in R||6h|
|Introduction to Machine Learning using Python: Introduction & Linear Regression||6h|
|Introduction to Machine Learning using Python: Classification||6h|
|Introduction to Machine Learning using Python: SVM & Unsupervised Learning||3h|