Upcoming SciNet Events

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July,2020
Tue 7th Jul
11:00 am
12:00 pm
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This seven-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. The programming language will be Python 3.7; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Location: SciNet Online
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Tue 7th Jul
12:30 pm
2:00 pm
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Learn the basics of Message Passing Interface (MPI) programming. Examples and exercises will be based on parallelization of common scientific computing problems.  Location: SciNet Online
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Wed 8th Jul
12:30 pm
2:00 pm
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Learn the basics of Message Passing Interface (MPI) programming. Examples and exercises will be based on parallelization of common scientific computing problems.  Location: SciNet Online
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Thu 9th Jul
11:00 am
12:00 pm
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This seven-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. The programming language will be Python 3.7; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Location: SciNet Online
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Thu 9th Jul
12:30 pm
2:00 pm
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Learn the basics of Message Passing Interface (MPI) programming. Examples and exercises will be based on parallelization of common scientific computing problems.  Location: SciNet Online
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Tue 14th Jul
11:00 am
12:00 pm
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This seven-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. The programming language will be Python 3.7; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Location: SciNet Online
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Tue 14th Jul
12:30 pm
2:00 pm
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Introduction to the neuroimaging data and best practices for the analysis of neuroimaging data using High Performance Clusters (HPC). We will introduce types of neuroimaging scanning modalities with instructions for how to organize these data using the Brain Imaging Data Structure (BIDS). We will then introduce Singularity container software (BIDS-apps) for the preprocessing of neuroimaging data (including mriqc and fmriprep) and demonstrate how to run them on the HPC. We will discuss general information about running Singularity containerized software on the HPC and how to construct custom containers for your own analysis using NeuroDocker. Location: SciNet Online
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Wed 15th Jul
12:30 pm
2:00 pm
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Introduction to the neuroimaging data and best practices for the analysis of neuroimaging data using High Performance Clusters (HPC). We will introduce types of neuroimaging scanning modalities with instructions for how to organize these data using the Brain Imaging Data Structure (BIDS). We will then introduce Singularity container software (BIDS-apps) for the preprocessing of neuroimaging data (including mriqc and fmriprep) and demonstrate how to run them on the HPC. We will discuss general information about running Singularity containerized software on the HPC and how to construct custom containers for your own analysis using NeuroDocker. Location: SciNet Online
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Thu 16th Jul
11:00 am
12:00 pm
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This seven-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. The programming language will be Python 3.7; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Location: SciNet Online
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Thu 16th Jul
12:30 pm
2:00 pm
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Introduction to the neuroimaging data and best practices for the analysis of neuroimaging data using High Performance Clusters (HPC). We will introduce types of neuroimaging scanning modalities with instructions for how to organize these data using the Brain Imaging Data Structure (BIDS). We will then introduce Singularity container software (BIDS-apps) for the preprocessing of neuroimaging data (including mriqc and fmriprep) and demonstrate how to run them on the HPC. We will discuss general information about running Singularity containerized software on the HPC and how to construct custom containers for your own analysis using NeuroDocker. Location: SciNet Online
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Tue 21st Jul
11:00 am
12:00 pm
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This seven-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. The programming language will be Python 3.7; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Location: SciNet Online
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Tue 21st Jul
12:30 pm
2:00 pm
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Get familiar with how one can manipulate and transform neuroimaging data using Python s neuroimaging packages (nibabel, nilearn). Develop an understanding how MRI data is represented in Python and perform some hands-on tasks such as basic manipulation on both structural MR and functional MR. Then we will discuss the steps required to take minimally pre-processed MR data (fmriprep), to clean and workable data through the process of motion cleaning and dimensionality reduction. Finally, we will cover how to perform functional connectivity (FC) analysis to build a resting state connectivity matrix. All analyses will be performed using Jupyter notebooks in the spirit of reproducible and open science. Location: SciNet Online
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Wed 22nd Jul
12:30 pm
2:00 pm
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Get familiar with how one can manipulate and transform neuroimaging data using Python s neuroimaging packages (nibabel, nilearn). Develop an understanding how MRI data is represented in Python and perform some hands-on tasks such as basic manipulation on both structural MR and functional MR. Then we will discuss the steps required to take minimally pre-processed MR data (fmriprep), to clean and workable data through the process of motion cleaning and dimensionality reduction. Finally, we will cover how to perform functional connectivity (FC) analysis to build a resting state connectivity matrix. All analyses will be performed using Jupyter notebooks in the spirit of reproducible and open science. Location: SciNet Online
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Thu 23rd Jul
11:00 am
12:00 pm
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This seven-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. The programming language will be Python 3.7; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Location: SciNet Online
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Thu 23rd Jul
12:30 pm
2:00 pm
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Get familiar with how one can manipulate and transform neuroimaging data using Python s neuroimaging packages (nibabel, nilearn). Develop an understanding how MRI data is represented in Python and perform some hands-on tasks such as basic manipulation on both structural MR and functional MR. Then we will discuss the steps required to take minimally pre-processed MR data (fmriprep), to clean and workable data through the process of motion cleaning and dimensionality reduction. Finally, we will cover how to perform functional connectivity (FC) analysis to build a resting state connectivity matrix. All analyses will be performed using Jupyter notebooks in the spirit of reproducible and open science. Location: SciNet Online
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Tue 28th Jul
11:00 am
12:00 pm
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This seven-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. The programming language will be Python 3.7; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Location: SciNet Online
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Tue 28th Jul
12:30 pm
2:00 pm
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Parallel programming in Python with a focus on parallel data analysis. We will cover subprocess, multiprocessing and other parallel-enabling python packages. Location: SciNet Online
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Wed 29th Jul
12:30 pm
2:00 pm
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Parallel programming in Python with a focus on parallel data analysis. We will cover subprocess, multiprocessing and other parallel-enabling python packages. Location: SciNet Online
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Thu 30th Jul
11:00 am
12:00 pm
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This seven-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. The programming language will be Python 3.7; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected. Location: SciNet Online
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Thu 30th Jul
12:30 pm
2:00 pm
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Parallel programming in Python with a focus on parallel data analysis. We will cover subprocess, multiprocessing and other parallel-enabling python packages. Location: SciNet Online
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August,2020
Tue 4th Aug
12:30 pm
2:00 pm
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Learn how to model the neural network in the brain using Python. Location: SciNet Online
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Wed 5th Aug
12:30 pm
2:00 pm
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Learn how to model the neural network in the brain using Python. Location: SciNet Online
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Thu 6th Aug
12:30 pm
2:00 pm
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Learn how to model the neural network in the brain using Python. Location: SciNet Online
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Tue 11th Aug
12:30 pm
2:00 pm
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Learn parallel programming R, with a focus on parallel data analysis. Location: SciNet Online
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Wed 12th Aug
12:30 pm
2:00 pm
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Learn parallel programming R, with a focus on parallel data analysis. Location: SciNet Online
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Thu 13th Aug
12:30 pm
2:00 pm
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Learn parallel programming R, with a focus on parallel data analysis. Location: SciNet Online
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Tue 18th Aug
12:30 pm
2:00 pm
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Learn how to perform data cleaning and statistical analysis of large scale genetic data using PLINK and R software. We will use SciNet to run the PLINK analytical workflow to perform markers and individuals quality control, including population stratification and ancestry followed by association analysis between genetic variation and trait of interest. R-software (basic R plotting and ggplot package) will be use to visualize the results. Location: SciNet Online
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Wed 19th Aug
12:30 pm
2:00 pm
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Learn how to perform data cleaning and statistical analysis of large scale genetic data using PLINK and R software. We will use SciNet to run the PLINK analytical workflow to perform markers and individuals quality control, including population stratification and ancestry followed by association analysis between genetic variation and trait of interest. R-software (basic R plotting and ggplot package) will be use to visualize the results. Location: SciNet Online
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Thu 20th Aug
12:30 pm
2:00 pm
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Learn how to perform data cleaning and statistical analysis of large scale genetic data using PLINK and R software. We will use SciNet to run the PLINK analytical workflow to perform markers and individuals quality control, including population stratification and ancestry followed by association analysis between genetic variation and trait of interest. R-software (basic R plotting and ggplot package) will be use to visualize the results. Location: SciNet Online
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Tue 25th Aug
12:30 pm
2:00 pm
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Debugging and profiling are important steps 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 with gdb and the debugging of parallel (MPI and threaded) codes. Location: SciNet Online
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Wed 26th Aug
12:30 pm
2:00 pm
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Debugging and profiling are important steps 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 with gdb and the debugging of parallel (MPI and threaded) codes. Location: SciNet Online
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Thu 27th Aug
12:30 pm
2:00 pm
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Debugging and profiling are important steps 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 with gdb and the debugging of parallel (MPI and threaded) codes. Location: SciNet Online
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September,2020
Tue 8th Sep
11:00 am
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This course is to introduce graduate students to the programing language Python. The course will teach the students how to install Python on their laptop and then use Python to perform data analysis. The course consists of twelve hands-on sessions, each lasting one hour, where students bring their own laptops and perform assignments, each of these assignments being due for the following lecture. Part of BCH2024H Introduction to Programming in Python
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