Title: Onboarding Author: Neil Ernst Date: 2018-06-20
This is your jumping off point to get you up and running with your work in collaboration with Dr. Ernst.
I prefer to be called Neil and addressed he/him.
Your first day
- Read the research ethics guidelines. Chat with Neil if you have any questions about lab norms or would like to add or change anything in the code of conduct.
- Join the slack channel by asking Neil to send you an invite.
Tools
In my work I use the following. I prefer if you do as well. If you want to use Word, for instance, please have a good reason (usually, some funding agency only accepts Word).
- Github
- Git
- Python & Scipy/Pandas & PyStan
- R (less often)
- Excel! Spreadsheets are great for data exploration.
- Slack
Latex
- Sharelatex/Authorea - sometimes, more often plain Latex over Git.
- SublimeText for Mac and the Latextools Plugin
- Bibtex! Everything you read you should stick in Bibtex. Checkout doi2bib.org.
Compute Canada and WestGrid
forthcoming
Courses and Skillsets
MSc. Students need to take 5 courses and the Research Skills course (595). A few recommendations:
- Documenting and Understanding Software Systems - Topics in Software Applications CSC 578A my Documentation course
- Data Mining TPCS:SOFTWARE APPLICATION: Data Mining CSC 578D
- ML theory : TPCS:ARTIFICIAL INTELGNCE: Machine Learning Theory CSC 581B
- CSC 511 Information Visualization
- CSC578B: Topics in Software Applications: "Computer-Supported Collaborative Work"
- CSC581C: Topics in Artificial Intelligence
And others as you (and I) see fit. There is a breadth requirement as well but I have no idea how that works yet, to be honest. Check with the graduate handbook. I think these courses should cover the breadth.
Useful online courses
- https://www.coursera.org/learn/statistical-inferences
- https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about
- https://www.coursera.org/learn/machine-learning
- https://xcelab.net/rm/statistical-rethinking/
Being a good researcher/student
I have a few resources here (there are tons). The first is all the links on Michael Ernst's page. These are all well worth reading. If you are not a strong writer, you should definitely pay attention to the advice on writing. But part of my job is to help you with that (modulo some basic ability).
The mandatory reading for this onboarding is Matt Might's Illustrated Guide to a PhD. It's a beautiful description of the frustration and wonder of conducting research.
I have a copy of "Getting What You Came For" in my office.
Other expectations
- see my expectations
- tackle some of these readings