Scientific Computing Fundamentals for Researchers
May 27th - May 31th, 2019
Register with CAMH email
The workshop series is FREE for all CAMH students, staff, and trainees
Please sign up with a CAMH email address, so that we know who you are!.
WHY?
Our research is increasingly more computationally-driven and training is often not part of the core curriculum for biomedical / medical science degrees. The Scientific Computing Workshops at CAMH are focused on building computing skills and fundamentals to help organize study data, automate repeatable/reproducible analyses, and make use of CAMH computing resources to save time. The workshops offer a range of topics and support different levels of experience. We use a shared dataset - spanning demographic, cognitive, imaging, and genomic data - across all workshop, maintaining consistency across the series. If you have questions, send us an email at SCWG@camh.ca
Required Software
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Click to see which software should be installed before you come to the workshops. For more detailed installation instructions go here.
Send us email if you are having trouble.
Linux/Shell (windows users only)
- Git for Windows which includes a BASH shell
- mobaXterm for remote access
MATLAB
- MATLAB free trial version
- mobaXterm for remote access (Windows only)
MS Access
- remote.camh.ca for basic remote access (you’ll need to install Citrix Receiver)
Python
R
REDCap
SCC
Spreadsheets
- Excel via remote.camh.ca (you’ll need to install Citrix Receiver). Or download OpenOffice for free.
SPSS
Version Control with Git
- Git for Windows
- Source Tree (optional; Mac and Windows only)
- SmartGit (optional; all platforms)
Calendar of Events
Course Descriptions
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Introduction to Programming Logic - Mon 27 @ 09:00 AM - 10:00 AM, CS 12th Floor (KCNI), RadianceInstructor: Leon French
Helper(s): Derek Howard
Who is this course for: Come here if you'd like to learn about programming, but have little to no prior experience. This will be an interactive workshop where you will play a game to learn new concepts.
You'll learn:
- What is programming, anyway?
- Essential programming concepts, such as sequencing, loops, conditionals, functions, variables, and datatypes
Course material:
You'll need: Please bring a laptop. We'll be working with python, but you don't need it installed.
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Introduction to Linux & Automation with Bash - Mon 27 @ 10:00 AM - 12:00 PM, CS 12th Floor (KCNI), RadianceInstructor: Nikola Bogetic
Helper(s): Andy Wang
Who is this course for:
You'll learn:
- About Linux & Bash
- Working with files and directories
- Searching and filtering
- Command chaining
- Loops
- Scripts
You'll need: Please bring a laptop. A temporary user account will be provided to you.
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Managing Code and Experiments with Git - Mon 27 @ 01:00 PM - 03:00 PM, CS 12th Floor (KCNI), RadianceInstructor: Qing and John
Helper(s): Ricardo
Who is this course for: Any one who is interested in managing code more effectively.
You'll learn:
This course will introduce the best practices of managing code and data with Git for reproducible and well documented scientific algorithms. Students will also learn various git commands that allow personal data/code storage as well as git commands for working collaboratively with others. Prerequisites: No prerequisites required
Course material: Provided in the workshop
You'll need: Please bring a laptop.
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Introduction to XNAT - Tue 28 @ 09:00 AM - 10:30 AM, CS 12th Floor (KCNI), ClarityInstructor: Jay Hennessey
Helper(s): Marcia Hon
Who is this course for:
You'll learn:
XNAT is a comprehensive database for the storage and management of medical imaging data including MRI, PET, EEG, CT, as well as other types of binary data such as gait measures and pathology. In this course, we follow a complete workflow starting with the use of Subject Registry, followed by XNAT, and finally Spotfire. Prerequisites: None
You'll need: Please bring a laptop.
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Introduction to LabKey - Tue 28 @ 10:30 AM - 12:00 PM, CS 12th Floor (KCNI), ClarityInstructor: Marcia Hon
Who is this course for: CAMH Staff who are interested in using LabKey as part of the Neuroinformatics Platform.
You'll learn:
LabKey enables tracking of genomics and other 'omics workflows, and managing and sharing resulting datasets. In this course, we follow a complete workflow with LabKey and Spotfire. For more information, please visit the LabKey wiki at http://neurowiki.camh.ca/mediawiki/index.php/LabKey Prerequisites: No prerequisites required
Course material: Provided in the workshop
You'll need: Please bring a laptop.
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REDCap Best Practices and New Features - Tue 28 @ 11:00 AM - 12:30 PM, CS 12th Floor (KCNI), RadianceInstructor: Steve and Natalia
Who is this course for: CAMH Staff who are interested in using REDCap as part of the Neuroinformatics Platform.
You'll learn:
In this class we’ll look at some best practices for REDCap project design and cover 10 steps that you can follow to ensure that you are collecting high quality data for your study. Prerequisites: No prerequisites required
Course material: Provided in the workshop
You'll need: Please bring a laptop.
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Best Practices for MS Excel - Tue 28 @ 01:00 PM - 03:00 PM, CS 12th Floor (KCNI), RadianceInstructor: Gabrielle
Helper(s): Nathan
Who is this course for: Anyone who wants to pick up some Excel tips & tricks. The sample datasets will be fairly clinical.
You'll learn:
- Spreadsheet structure, cell referencing, and functions
- Cleaning, organizing, and aggregating data
- Ways to summarize a spreadsheet: pivot tables, lookups, and formatting
Course material:
You'll need: A laptop with MS Excel (some laptops will be available onsite)
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Building a Participant Tracking Database in MS Access - Tue 28 @ 03:00 PM - 05:00 PM, CS 12th Floor (KCNI), RadianceInstructor: Steve
Who is this course for: Anyone interested in Access.
You'll learn:
In this class, our goal is to build a simple recruitment tracking database. You will learn:
*The differences between Excel vs. Access and when you should use each
*Database design
*Building tables, forms and queries
*Summarizing your data with pivot tables and reports Prerequisites: No prerequisites required
Course material: Provided in the workshop
You'll need: Please bring a laptop.
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Introduction into SQL - Tue 28 @ 09:01 AM - 11:00 AM, CS 12th Floor (KCNI), RadianceInstructor: Natalia Potapova
Helper(s): Nikola Bogetic
Who is this course for:
You'll learn:
Basic SQL syntax:- SQL commands
- filtering records
- quering data from multiple tables
- grouping records to calculate means etc
Course material: Provided in the workshop
You'll need: You will need to bring your own laptop. Please install Toad [link will be provided later] on your laptop.
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R for SPSS Users - Wed 29 @ 09:00 AM - 11:00 AM, CS 12th Floor (KCNI), ClarityInstructor: Marcos Sanches
Helper(s):
Who is this course for: Users of SPSS who wish to transition to R.
You'll learn:
In this workshop you will learn how to get started with R and RStudio, the R environment and how R works with datasets and objects. We will initially build a simple dataset from scratch. Then we will import an SPSS dataset into R and do some basic descriptive statistics in R. We will not get into advanced statistics or programming, but rather try to give you a foundation of basic knowledge in R so that you can build on that as you need. You are expected to bring a laptop with R and RStudio installed. Prerequisites: None
You'll need: Please bring a laptop.
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Introduction to R and RStudio - Wed 29 @ 01:00 PM - 03:00 PM, CS 12th Floor (KCNI), RadianceInstructor: Erin
Who is this course for:
You'll learn:
You’ll learn:- Reading you data into and R dataframe
- Sorting/merging/filtering your data tables
- Getting summary statistics
You'll need: Please bring a laptop with R and R studio installed.
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R Analysis and Visualization - Wed 29 @ 03:00 PM - 05:00 PM, CS 12th Floor (KCNI), RadianceInstructor: Erin
Who is this course for:
You'll learn:
You’ll learn: Reorganize/Reshape your dataset with tidyr and dplyr Quickly create stats tables Plotting and visualization with ggplot2 Prerequisites: Basic familiarity with R (i.e. Introduction to R)
You'll need: Please bring a laptop with R and R studio installed.
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Introduction to Machine Learning - Thu 30 @ 09:00 AM - 11:00 AM, CS 12th Floor (KCNI), RadianceInstructor: Jerrold Jeyachandra
Helper(s): Ricardo Harripaul
Who is this course for: Individuals who'd like an introductory overview to machine learning algorithms with focus on how to create generalizable models whilst avoiding common pitfalls
You'll learn:
- bulleted list
- Supervised and Unsupervised learning
- Model selection and validation
Course material: Slides will be published soon
You'll need: Please bring a laptop.
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Analysis in Python - Thu 30 @ 01:00 PM - 03:00 PM, CS 12th Floor (KCNI), RadianceInstructor: Jerrold Jeyachandra
Helper(s): Ricardo Harripaul, Michael Joseph
Who is this course for: Students and Staff looking to learn a versatile language to automate their daily workflows and perform analysis
You'll learn:
- bulleted list
- Spreadsheet manipulation programmatically using Python and Pandas
- Performing computations on tabular data
Course material: Content will be published soon
You'll need: Please bring a laptop with Python 3 installed. Virtualenv/Anaconda is preferable. We can provide a web-based python programming environment as well
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Machine Learning in Python - Thu 30 @ 03:00 PM - 05:00 PM, CS 12th Floor (KCNI), RadianceInstructor: Ricardo Harripaul
Helper(s): Jerrold Jeyachandra
Who is this course for: Individuals looking to learn how to use popular machine learning packages developed in Python such as scikit-learn to train classification and regression learning algorithms
You'll learn:
- bulleted list
- Using scikit-learn to train machine learning models
- Implement cross-validation and experiment with bias-variance tradeoffs
Course material: Content will be published soon
You'll need: Please bring a laptop with Python 3 installed as well as scikit-learn, matplotlib. Preferably you will use virtualenv/anaconda. We provide web-based programming environments as well; you'll just need a laptop
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Introduction to CAMH Compute Cluster - Fri 31 @ 09:00 AM - 10:00 AM, CS 12th Floor (KCNI), RadianceInstructor: Nikola Bogetic
Helper(s): Andy Wang
Who is this course for:
You'll learn:
- About the CAMH Compute Cluster
- What compute resources are available.
- How to submit processing jobs to the queue.
- How the cluster queue handles requests.
- Data transfer / management best-practices.
Course material: Provided in the workshop
You'll need: Please bring a laptop. A temporary user account will be provided to you. Software to connect to the cluster is also provided.
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Parallel Computing (CAMH Compute Cluster) - Fri 31 @ 10:00 AM - 12:00 PM, CS 12th Floor (KCNI), RadianceInstructor: Nikola Bogetic
Helper(s): Andy Wang
Who is this course for:
You'll learn:
- Parallel Computing on the CAMH Compute Cluster.
- Writing scripts to run analyses in parallel.
- Submitting parallel jobs to the CAMH Cluster .
- GNU Parallel & ‘qbatch’ packages.
Course material: Provided in the workshop
You'll need: Please bring a laptop. A temporary user account will be provided to you. Software to connect to the cluster is also provided.
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Introduction to MATLAB - Fri 31 @ 01:00 PM - 03:00 PM, CS 12th Floor (KCNI), RadianceInstructor: Colin
Who is this course for:
You'll learn:
- Using the graphical MATLAB environment and workspace
- MATLAB data types (numeric, string) and structures (array, matrix, cell array)
- Basic mathematical operations
- Calling functions
- Reading from and writing to files
- Basic script syntax and control flow (if, for, while)
You'll need: A laptop with MATLAB installed (free trial: https://www.mathworks.com/campaigns/products/trials.html).