The following training events will be offered by SciNet in 2024/2025. Most events take place online, others are in-person in our teaching room at the SciNet offices on the St. George Campus of the University of Toronto (https://www.scinethpc.ca/contact-us/). Many of the events are recorded and posted afterwards on the sites listed below. All events listed below are free of charge. With a few exceptions, these training courses can be taken for SciNet certificate credits. To register for these events, log into https://scinet.courses with your Alliance/CCDB account, go to “Home”, select the course, and click on “Enrol me in this course”. A number of courses may still be added later for the Winter 2025 term. For any questions, contact courses@scinet.utoronto.ca
Introduction to Niagara and Mist
Date/time: Any Time | https://scinet.courses/1352
This is new, self-guided course. At your own pace, learn how to use the SciNet systems Niagara and Mist, from securely logging in to running computations on the supercomputer. Highly recommended for new users of Niagara and Mist, but experienced users may still pick up some valuable pointers!
Format: Self-guided
Counts towards the SciNet HPC Certificate.
Introduction to computational biostatistics with R
Tue and Thu, 10:00 am – 11:30 am ET starting Sep 10 | https://scinet.courses/1353
The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language. Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data. Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization. This is a UofT course restricted to graduate students, but could be audited upon request.
Format: In Person
Counts towards the SciNet Scientific Computing and Data Science Certificates
Introduction to Linux command line
- Mon Sep 16, 1:00 pm – 4:00 pm EDT | https://scinet.courses/1354
- Mon Nov 25, 1:00 pm – 4:00 pm EST | https://scinet.courses/1355
- Mon Mar 3, 1:00 pm – 4:00 pm EST | https://scinet.courses/1356
Working with many of the HPC systems (like those at SciNet) involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course which will cover basic commands. It could be a great boon for your productivity.
Format: Virtual
Counts towards the SciNet Scientific Computing Certificate
Introduction to supercomputing
Sep 23, 25, 27, 12:30 pm – 2:00 pm EDT | https://scinet.courses/1357
An introduction to basic concepts in High-Performance Computing (HPC). This is intended to be a high-level primer for those largely new to HPC. Topic will include motivation for HPC, available HPC resources, essential issues, problem characteristics as they apply to parallelism and a high-level overview of parallel programming models.
Format: Virtual
Counts towards the SciNet High Performance Computing Certificate
Securing file access permissions on Linux
Fri Oct 4, 1:00 – 3:00 pm EDT | https://scinet.courses/1360
Did you know the Linux operating system has built-in tools to control which specific users and groups can access which files and directories? In this session, you will learn what these Linux permissions are, how to use the available tools to control access and sharing, and how to avoid common security pitfalls.
Format: Virtual
Counts towards the SciNet Scientific Computing Certificate
Scaling up: mastering HPC
Mon Oct 28, 1:00 pm – 4:00 pm EDT | https://scinet.courses/1359
Learn how to fully utilize the power of HPC. Discover proven strategies and tools to efficiently scale up from serial jobs to parallel runs across many compute nodes on Niagara.
Format: In Person
Counts towards the SciNet High-Performance Computing Certificate
Introduction to programming with Python
Tue and Thu from Nov 5 to Dec 5, 1:00 pm – 2:00 pm EDT | https://scinet.courses/1362
New to programming? Learn the basics of programming using the Python programming language in eight one-hour sessions over the course of five weeks. Sessions will consist of a mix of lectures and hands-on exercises.
Format: In Person
Counts towards the SciNet Scientific Computing Certificate
Introduction to Apptainer
Fri Nov 29, 1:00 – 4:00 pm EST | https://scinet.courses/1363
Container computing is gradually changing the way researchers are developing, sharing, and running software applications. Apptainer (formerly called Singularity) is gaining popularity in HPC for its performance, ease of use, portability, and security. In this course, we will explore: what is a container, why use a container, and how to use and create one.
Format: Virtual
Counts towards the SciNet Scientific Computing Certificate
Linux shell scripting
- Fri Oct 25, 1:00 – 4:00 pm EDT | https://scinet.courses/1364
- Mon Jan 20, 1:00 – 4:00 pm EST | https://scinet.courses/1365
- Mon Apr 8, 1:00 – 4:00 pm EDT | https://scinet.courses/1366
Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some basic Linux command line experience.
Format: Virtual
Counts towards the SciNet Scientific Computing Certificate
Git version control
Wed Nov 6, 1:00 pm – 4:00 pm EST | https://scinet.courses/1367
Using version control for your scripts, codes, documents, papers, and even data, allows you to track changes, keep backups, and facilitate collaboration. In this workshop, you will learn the basics of version control with the popular distributed version control software GIT. This workshop assumes that students have an understanding of basic Linux shell commands.
Format: Virtual
Counts towards the SciNet Scientific Computing Certificate
Introduction to parallel programming
Dec 2, 4, 6, 12:30 pm – 2:00 pm EST | https://scinet.courses/1368
An introduction to concepts and techniques in parallel computing with compiled languages, e.g., C, C++ or Fortran. Both OpenMP and MPI will be introduced.
Format: Virtual
Counts towards the SciNet High Performance Computing Certificate
Scientific computing for physicists
Tue and Thu, 11:00 am – 12:00 pm ET, starting Jan 9 | https://scinet.courses/1369
This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, …). This is a UofT course restricted to graduate students, but could be audited online upon request.
Format: In Person
Counts towards the SciNet Scientific Computing and High Performance Certificates
Quantitative applications for data analysis
Winter 2025 | TBD
In this course data analysis techniques utilizing the Python and R languages will be introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students for performing scientific data analysis. Successful students will learn how to use statistical inference tools to gain insight into large and small data sets, as well as be exposed to cutting-edge techniques and best practises to store, manage and analyze (large) data. Topics include: Python and R programming, version control, automation, modular programming and scientific visualization. This is a UofT course restricted to graduate students, but could be audited online upon request.
Format: In Person
Counts towards the SciNet Scientific Computing and Data Science Certificates
Bash command line with common idioms, AWK, And Others
Mon Feb 3, 1:00 pm – 4:00 pm EDT | https://scinet.courses/1370
This workshop explores various concise and useful constructs for working with bash shell. The goal is to improve your shell skills. Attending this class requires some basic GNU/Linux command line experience.
Format: Virtual
Counts towards the SciNet Scientific Computing Certificate
Neural network programming
Starting in April 2025 | TBD
This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts.
Format: TBD
Counts towards the SciNet Data Science Certificate
Python and High Performance Computing
Tue Apr 22, 1:00 pm – 4:00 pm EDT | https://scinet.courses/1371
Parallel programming in Python. We will cover subprocess, numexpr, multiprocessing, MPI, and other parallel-enabling python packages.
Format: Virtual
Counts towards the SciNet High Performance Computing Certificate
Parallel debugging with DDT
Mon Apr 28, 1:00 pm – 4:00 pm EDT | https://scinet.courses/1373
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this session, we will discuss the debugging of frequently encountered bugs in serial code and debugging of parallel (MPI and threaded) codes using DDT.
Format: Virtual
Counts towards the SciNet High Performance Computing Certificate
Relational database basics
Mon May 5, 1:00 pm – 4:00 pm EDT | https://scinet.courses/1372
Principles and uses of relational databases with practical examples using Python and Sqlite on the Niagara supercomputer.
Format: Virtual
Counts towards the SciNet Data Science Certificate
2025 Compute Ontario Summer School
June 2025, tentative, dates TBD | https://training.computeontario.ca
The Compute Ontario Summer School, jointly organized by SHARCNET, SciNet, Centre for Advanced Computing, and in collaboration with the RDM Network of Experts, offers a comprehensive curriculum packed with dozens of courses for researchers, students, and staff. These sessions are offered in parallel streams which cover a wide range of topics including Advanced Research Computing (ARC), High Performance Computing (HPC), and Research Data Management (RDM) and are available at introductory to advanced levels. Whether you are interested in a specific topic or wish to explore multiple areas, you have the freedom to register for one, some, or all of the workshops available.
Format: Virtual