DATA ANALYSIS with R
Workshop Facilitator: Jie Jian, MSc
Jie Jan has been a sessional lecturer at the Department of Mathematics and Statistics, Thompson Rivers University since she got her Masters degree in Applied and Computational Mathematics from Simon Fraser University in 2018. Prior to that, she obtained her Bachelors degree in Statistics from Huazhong University of Science and Technology in 2016. Her research interest lies in data modelling and solving complicated problems with machine learning tools. Experience gained across several diverse projects has enabled her to hone very strong coding skills in R, MATLAB, Python, etc.
R is a programming language and free software environment for statistical computing and graphics. R provides an open source route to easily apply a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering) and graphical techniques, and is highly extensible.
In this workshop participants will take their first steps with R. The objective of this workshop will focus on creating new variables to conduct basic calculations, getting data to R, conducting simple statistics and visualization with R, and then introducing linear regression and decision tree models with applications in R.
No prior experience with R is required.
Download R here before the workshop:https://www.r-project.org/
DATA VISUALIZATION with PYTHON
Workshop Facilitator: Alex Razoumov, PhD
Alex Razoumov is a Training and Visualization Coordinator for WestGrid and the Team Lead for Compute Canada's national Visualization Team. Alex earned his PhD in computational astrophysics from the University of British Columbia, and in his astrophysicist days worked on numerical models ranging from galaxy formation to core-collapse supernovae and stellar hydrodynamics, and has developed a number of computational fluid dynamics and radiative transfer codes and techniques. He spent five years as HPC Analyst in SHARCNET helping researchers from diverse backgrounds to use large clusters, and in 2014 joined WestGrid. Alex presently lives in Vancouver, British Columbia.
In this workshop, participants will learn to perform (2D/3D) data visualization using Python 3 along with Paraview. Participants will have an opportunity to familiarise themselves with a subset of the data they will work with during the Data Visualisation competition, and perform a series of exercises to visualise it.
For your OS install ParaView from http://www.paraview.org/download
For your OS install Python3.7 Miniconda distribution from http://conda.pydata.org/miniconda.html
Start the command-line shell (terminal in MacOS/Linux, DOS prompt in Windows) and then install the required Python packages:
`conda install numpy vtk`
INTRODUCTION TO GITHUB
Workshop Facilitator: Dan Fornika, MSc
Dan is a Genomics Specialist at the BC Centre for Disease Control Public Health Lab. He has made contributions to several popular open-source bioinformatics repositories on GitHub, including galaxy, kraken and the bioconda project.
For more info about Dan, click here.
GitHub is a popular platform for working collaboratively on software and data projects. This workshop will focus on introducing the features of GitHub that facilitate collaboration. Participants will learn how to propose and discuss changes to a repository. We will discuss ways to manage changes in a safe and controlled manner by using GitHub features such as 'branches' and 'Pull Requests'.
Some basic familiarity with version control using GitHub.
Register for your own GitHub account here before attending the workshop: https://github.com/
Workshop Facilitator: Michael Monagan, PhD
Michael Monagan has been a professor of mathematics at Simon Fraser University since 1995. Michael earned his PhD in computational mathematics at the University of Waterloo in 1990. He is one of the main authors of Maple and continues to be involved with the development of Maple. His current research involves developing parallel algorithms for factoring polynomials and computing GCDs of polynomials. He is currently supervising four graduate students at SFU.
Maple is a general purpose mathematics system with a large library of tools for computations in many areas of mathematics. It is a programming language like Matlab, but has facilities for exact computation; it will produce formulas for integrals, factor polynomials over finite fields, and solve systems of polynomials with an infinite number of solutions.
In the workshop I will introduce basic tools for doing calculus in one and two variables, generating 2D and 3D plots of curves and surfaces, demo the graph theory package for fun, and then we'll do some experiments with calculating integrals and visualizing eigenvectors.
No prior knowledge of Maple is assumed.