Calendar

DESCRIPTION (PARTS 1 AND 2): Introduction of neural network programming concepts, theory and techniques. The class material will being at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate concepts.

DESCRIPTION (PART 3): This part will continue the development of the neural network programming approaches from Parts 1 & 2. This part will focus on methods used to generate sequences: LSTM networks, sequence-to-sequence networks, and transformers.

TEACHER: Erik Spence (SciNet, University of Toronto)

LEVEL: Introductory

FORMAT: Lecture + Hands-on

CERTIFICATE: Attendance

PREREQUISITES:

* Experience with Python will be assumed. (This course is being taught assuming this.)
* No prior experience with the Keras neural framework is expected. (The Keras neural framework will be used for neural network programming.)

DESCRIPTION: Running programs on the supercomputers is done via the Bash shell. This course is three one hour lectures on using bash. No prior familiarity with bash is assumed. In addition to the basics of getting around, globbing, regular expressions, redirection, pipes, and scripting will be covered.

TEACHER: Tyson Whitehead (SHARCNET, Western University)

LEVEL: Introductory

FORMAT: Lecture + Exercises with Questions

CERTIFICATE: Attendance and Completion

PREREQUISITES: None

DESCRIPTION: Running programs on the supercomputers is done via the Bash shell. This course is three one hour lectures on using bash. No prior familiarity with bash is assumed. In addition to the basics of getting around, globbing, regular expressions, redirection, pipes, and scripting will be covered.

TEACHER: Tyson Whitehead (SHARCNET, Western University)

LEVEL: Introductory

FORMAT: Lecture + Exercises with Questions

CERTIFICATE: Attendance and Completion

PREREQUISITES: None

DESCRIPTION: Have you ever tried to run someone else's code and it just didn't work? Have you ever been lost interpreting your colleague's data? This hands-on session will provide researchers with tools and techniques to make their research process more transparent and reusable in remote computing environments. We'll be using platforms like JupyterHub and scripting languages like Bash to demonstrate the material. In this workshop, you'll learn about:

* Organizing your file directories
* Writing readable metadata with README files
* Automating your workflow with scripts
* Capture and share your computational environment
Using large language models (GenAI) to assist with the above

TEACHERS: Sarah Huber (University of Victoria), Shahira Khair (University of Victoria), and Drew Leske (University of Victoria)

LEVEL: Introductory

FORMAT: Lecture + Hands-on

CERTIFICATE: Attendance

PREREQUISITE: Familiarity with command-line tools in a Unix environment is not a requirement for the workshop but may be helpful for some of the hands-on activities.