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| April,2024 | |
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10 Apr 11:00 am 12:00 pmIntro to Python for BiochemistryIn this course students will be instructed in how to program in Python. Ultimately students will learn how to use Python to analyze, process and visualize data. This course is designed for students with little to no experience in programming. This is a graduate course that can be taken for by UofT Biochemistry graduate students. Those students should enrol using ACORN/ROSI. | BCH2203 - Winter 2024 |
10 Apr 1:00 pm 2:30 pmIntro to NiagaraIn about 90 minutes, learn how to use the SciNet systems Niagara and Mist, from securely logging in to running computations on the supercomputer. Experienced users may still pick up some valuable pointers.Format: Virtual Virtual | HPC105 - Apr 2024 |
15 Apr 1:00 pm 4:00 pmShell ScriptingLearn how to write bash scripts, use environment variables, how to control process, and much more. Requires some Linux basic command line experience.Note: this event has been moved from April 8th to April 15th.Format: Virtual Virtual | SCMP201 - Apr 2024 |
17 Apr 12:00 pm 1:00 pmCO Colloquium "How to Buy a Supercomputer for Scientific Computing"Buying a new supercomputer that both maximises total performance, given our budget, and whose architecture suits our users' workloads is a very difficult balancing act. There are a wide range of decisions to be made, such as: CPU architecture; node count; memory size/bandwidth; GPU count; interconnect type; storage size; filesystem type/bandwidth; cooling type and power budget to name but a few. In order to balance all of these constraints we need to come up with a scoring system to compare potential candidate supercomputers. In this talk we describe the Scalable System Improvement (SSI) metric and apply it to the system refresh of Niagara & Mist. Virtual | COCO - 17 Apr 2024 |
23 Apr 11:00 am 12:00 pmDAT112: Lecture 1Introduction to neural network programming, lecture 1 | DAT112 - Apr 2024 |
25 Apr 11:00 am 12:00 pmDAT112: Lecture 2Introduction to neural network programming, lecture 2 | DAT112 - Apr 2024 |
30 Apr 11:00 am 12:00 pmDAT112: Lecture 3Introduction to neural network programming, lecture 3 | DAT112 - Apr 2024 |
| May,2024 | |
2 May 11:00 am 12:00 pmDAT112: Lecture 4Introduction to neural network programming, lecture 4 | DAT112 - Apr 2024 |
7 May 11:00 am 12:00 pmDAT112: Lecture 5Introduction to neural network programming, lecture 5 | DAT112 - Apr 2024 |
8 May 1:00 pm 2:30 pmIntro to NiagaraIn about 90 minutes, learn how to use the SciNet systems Niagara and Mist, from securely logging in to running computations on the supercomputer. Experienced users may still pick up some valuable pointers.Format: Virtual Virtual | HPC105 - May 2024 |
9 May 11:00 am 12:00 pmDAT112: Lecture 6Introduction to neural network programming, lecture 6 | DAT112 - Apr 2024 |
13 May 1:00 pm 4:00 pmRelational DatabasesPrinciples and uses of relational databases with practical examples using python and sqlite on the Niagara supercomputer.Prerequisites: Some Linux command line experience. Python experience is strongly advised. Format: Virtual Virtual | SCMP231 - May 2024 |
14 May 11:00 am 12:00 pmDAT112: Lecture 7Introduction to neural network programming, lecture 7 | DAT112 - Apr 2024 |
16 May 11:00 am 12:00 pmDAT112: Lecture 8Introduction to neural network programming, lecture 8 | DAT112 - Apr 2024 |
21 May 11:00 am 12:00 pmDAT112: Lecture 9Introduction to neural network programming, lecture 9 | DAT112 - Apr 2024 |
23 May 11:00 am 12:00 pmDAT112: Lecture 10Introduction to neural network programming, lecture 10 | DAT112 - Apr 2024 |
27 May 1:00 pm 4:00 pmBash idioms, awk, etc.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 | SCMP281 - May 2024 |
28 May 11:00 am 12:00 pmDAT112: Lecture 11Introduction to neural network programming, lecture 11 | DAT112 - Apr 2024 |
| June,2024 | |
3 Jun 9:00 am 12:00 pmCO Summer School S2: Data PreparationThis course provides you with essential knowledge and skills to effectively prepare data for analysis. Starting with an overview of the Data Analytics pipeline and processes, the course explores various statistical and visualization techniques used in Exploratory and Descriptive Analytics to understand historical data. You will then delve into the art of Data Preparation, gaining expertise in data cleaning, handling missing values, detecting, and handling outliers, as well as transforming and engineering features. By the end of the course, you will be equipped with the necessary tools to ensure data quality and integrity, enabling you to make informed decisions and derive valuable insights from their data. Level: Introductory Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Basic Python (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024 |
3 Jun 9:00 am 12:00 pmCO Summer School S1: Introduction to Linux shell (morning session)Running programs on the supercomputers is done via the BASH shell. This course is two three hour live demos 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. A series of exercises are required to be done in order to complete the course. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024 |
4 Jun 9:00 am 12:00 pmCO Summer School S2: Bioinformatics: Analysis of RNA-sequencing dataRNA-Seq refers to high throughput sequencing methods that probes the entire transcriptomic landscape of a given tissue or sample of interest. The data acquired from such experiments can be used to explore the overall RNA profile of a sample as well as comparing samples under various conditions. While extremely powerful, RNA-Seq is susceptible to numerous experimental pitfalls and requires intimate knowledge of the experimental procedures and data analysis methods. When conducted properly RNA-Seq can reveal information about gene/transcript expression, splicing and the effects of mutations. In this session we will take a thorough look at a comprehensive RNA-Seq pipeline, from sample processing methods to final differential expression analysis. Relevant R / BioConductor packages will be introduced. We will have the opportunity to investigate numerous quality control metrics, perform genomic alignment, differential expression and pathway enrichment analysis. We will cover several “gotcha”s and common mistakes in experimental design and data analysis. Basic familiarity with R and Linux command line will be beneficial but not required. All necessary commands and parameters will be explained during the class. Participants will be offered hands-on practice in which they will use RStudio to run R/BioConductor scripts for data analysis as well as the Integrative Genomic Viewer (IGV) software to visualize genomic data on their laptops Level: Intermediate Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Basic R and Linux beneficial but not required (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024 |
4 Jun 1:30 pm 4:30 pmCO Summer School S2: Bioinformatics: Long-read sequencing applicationsLong-read sequencing technologies enable the sequencing of DNA fragments 10KB and longer. This read length greatly improves sequence mappability and assembly, providing an advantage over short-read sequences that are difficult to map uniquely to repetitive and GC-rich regions. Long-read sequencing has applications in a number of fields including genome assembly, diagnosis of genetic diseases, and metagenomics. In this workshop, we will focus on PacBio HiFi sequences and introduce you to tools for haplotyping, calling and visualizing structural variants and repeat expansions, visualizing read methylation, and detecting novel isoforms from PacBio Iso-Seq data. Participants will be offered hands-on practice in which they will use RStudio to run R/BioConductor scripts for data analysis as well as the Integrative Genomic Viewer (IGV) software to visualize genomic data on their laptops Level: Intermediate Length: 3 Hours Format: Lecture + Hands-on Prerequisites: Basic R (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024 |
5 Jun 9:00 am 10:20 amCO Summer School S2: Research Data Management: Rationale for ReproducibilityThe role of good research data management practices in supporting research reproducibility is becoming increasingly well known. The literature is replete, however, with examples of poor methodology, lack of transparency, mistakes, and misconduct leading to bad science and an inability to reproduce results. This introductory session will provide real-world, illustrative examples of each of these, along with practical suggestions on how to avoid them. Level: Introductory Length: 1.5 Hours Format: Lecture Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024 |
5 Jun 1:30 pm 2:50 pmCO Summer School S2: Using generative AI tools for research data managementIn this workshop, we will explore the potential uses of generative artificial intelligence tools in research data management (RDM) with a focus on specific use cases. For example, can AI tools be used to write Data Management Plans, summarize funder requirements, assist with data analysis, or suggest file naming conventions and folder structures? This workshop will be interactive, and participants will be welcome to practice using AI tools along with the presenters using real-world data and prompts. We will also discuss the ethical considerations, including benefits and risks, of using AI tools in research and whether it is possible to use AI for RDM practices in an ethical manner. Level: Introductory Length: 1.5 Hours Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024 |
5 Jun 1:30 pm 4:30 pmCO Summer School S1: Introduction to Python (afternoon session)This course is designed to provide you with a solid foundation in Python programming language. Through a comprehensive curriculum and hands-on coding exercises, participants will learn the fundamentals of Python syntax, data types, functions, and file handling. By the end of the course, you will have gained the essential skills to write Python programs, solve problems, and build the foundation for more advanced Python development. Whether you are a beginner or have some programming experience, this course will equip you with the necessary tools to start your journey in Python programming. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024 |
6 Jun 1:30 pm 2:50 pmCO Summer School S2: Supporting research with Data Management Plans & the DMP Assistant!This session will provide participants with information, guidance, and resources for supporting research through the development and implementation of data management plans (DMPs). Level: Introductory Length: 1.5 Hours Format: Lecture Prerequisites: None General topics covered will include the importance and benefits of DMPs, their content, and impending DMP requirements relating to the Tri-Agency research data management (RDM) policy. Specific focus will be given to the Digital Research Alliance of Canada DMP Assistant platform that is hosted nationally at the University of Alberta Library, along with a new DMP template developed by the Alliance’s DMP Expert Group (DMPEG). This new template is targeted specifically to support researchers in meeting DMP requirements at the funding opportunity application stage. Additional information relating to an accompanying assessment rubric that is currently in development will be shared. Time will be reserved for questions and discussion. (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024 |
6 Jun 1:30 pm 4:30 pmCO Summer School S1: Introduction to RThis half-day session offers a brief introduction to R, with a focus on data analysis and statistics. We will discuss the following topics: the R interface, primitive data types, lists, vectors, matrices, and data frames - a crucial data type in data analysis and the trademark of the R language. Advanced topics to be covered include: basics statistics and function creation; *apply family functions; and the basics of scripting. Level: Introductory Length: 3 Hours Format: Lecture + Hands-on Prerequisite: Some programming experience in another programming language (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024 |
7 Jun 9:00 am 12:00 pmCO Summer School S1: Introduction to C (morning session)This course will provide hands-on experience on fundamental concepts of programming using C. This will include Conditional statement, Loops(while and for), Arrays, Pointers, Functions and Dynamic memory allocation. An introduction will be provided regarding fundamental data structures such as linked list, stacks, queues and binary trees. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024 |
7 Jun 1:30 pm 4:30 pmCO Summer School S1: Introduction to C (afternoon session)This course will provide hands-on experience on fundamental concepts of programming using C. This will include Conditional statement, Loops(while and for), Arrays, Pointers, Functions and Dynamic memory allocation. An introduction will be provided regarding fundamental data structures such as linked list, stacks, queues and binary trees. Level: Introductory Length: Two 3-Hour Sessions Format: Lecture + Hands-on Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024 |
7 Jun 3:00 pm 4:20 pmCO Summer School S2: Using Odesi for Survey and Public Opinion ResearchOdesi (odesi.ca) is a Canadian social science data repository and online data exploration and analysis tool. Odesi’s collections include over 5,700 historical and contemporary surveys and public opinion polls from a variety of data providers such as Statistics Canada and the Canadian Opinion Research Archive (CORA). This workshop will demonstrate how to effectively search for and access data within Odesi on a variety of social, economic, and political topics. Attendees will learn how to navigate the interface, using search features and available collections, explore survey questions (variables), perform basic tabulations and analysis using connected tools, and download datasets into statistical software (e.g. R, SPSS) for further analysis. Level: Introductory Length: 1.5 Hours Format: Lecture Prerequisites: None (part of the 2024 Compute Ontario Summer School) Virtual | COSS2024 |

