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Training and Education

Monday August 21, 2017 - 21:31
  

SciNet is a high-performance computing consortium of the University of Toronto and associated research hospitals, serving the computational needs of Canadian academic researchers. It is one of six such consortia in the Compute Canada family.

This website contains the online content of SciNet's training and education program. It contains lecture videos, slides, links, forums and other electronic material, all publicly available. The materials are organized by course; the list of recent courses can be browsed below.

SciNet users and students can furthermore login to submit assignments and track their progress towards SciNet's Scientific Computing Certificate, Data Science Certificate, and High Performance Certificate.

      Category  Starts        
HPC162 Advanced Parallel Scientific Computing (Sept. 2017)

Advanced Parallel Scientific Computing
HPC162

Explore use advanced examples of parallel computing in scientific research.
15 enrolled - 60 minutes 
High Performance Computing (university credit) 2017-09-12
MSC1090 Introduction to Clinical BioStatistics (Quantitative Applications for Data Analysis)

Introduction to Clinical BioStatistics
MSC1090

In this course data analysis techniques utilizing the R statistical language, will be discussed and introduced, as well as, the basics of programming and scientific computing. The goal of this course is to prepare graduate students to perform scienti...
1 enrolled - 60 minutes 
Data Science (university credit) 2017-09-12
SciNet User Group Meeting (Sept. 2017)

SciNet User Group Meeting

Pizza, user discussion, and a tech talk:
ChIP-Seq analysis of the Interactive Bromodomain 1 protein (Ibd1) in Tetrahymena thermophila, by PhD student Alejandro Saettone (Ryerson University)
- 60 minutes 
SNUG 2017-09-13
DAT212 Advanced Neural Networks (Oct 2017)

Advanced Neural Networks
DAT212

This class will review advanced neural network programming theory and architectures. The level of the material will not be introductory, experience with neural networks will be assumed. This class is intended to continue the material covered in DAT...
15 enrolled - 4 events of 60 minutes 
Data Science 2017-10-02
SCMP112 Intro to Scientific Computing with Python (Nov.2017)

Intro to Scientific Computing with Python
SCMP112

Learn about research computing even with little programming experience. Covers basics of programming in python, best practices and visualization. The course will last 4-6 weeks with 2 lectures per week (mini/modular grad course).
2 enrolled - 60 minutes 
Scientific Computing (university credit) 2017-11-01
PHY1610 Scientific Computing for Physicists (Winter 2018)

Scientific Computing for Physicists
PHY1610

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 c...
1 enrolled - 60 minutes 
Scientific Computing (university credit) 2018-01-09

Archived Courses and Events

HPC160 Compute Ontario Summer School - Central (July 2017)

Compute Ontario Summer School - Central
HPC160

A week-long, three-stream intensive workshop on high performance computing, parallel programming, visualization and data science. Up to 30 credits towards SciNet certificates
- 28 events of 180 minutes 
High Performance Computing 2017-07-28
Scaling to Petascale Institute

Scaling to Petascale Institute

A virtual HPC summer school, organized by a number of the US XSEDE sites, also hosted at SciNet. Details at https://bluewaters.ncsa.illinois.edu/petascale-summer-institute .
- 6240 minutes 
External 2017-06-26
SCMP231 Relational Database Basics (June 2017)

Relational Database Basics
SCMP231

Principles and uses of relational databases with practical examples using python and sqlite.
Attended: 8 - 420 minutes 
Data Science 2017-06-21
HPC105 Intro to SciNet

Intro to SciNet
HPC105

In about 60 to 90 minutes, you will learn how to use the SciNet systems. Experienced users may still pick up some valuable pointers.
Attended: 9 - 90 minutes 
High Performance Computing 2017-06-14


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