/JSC370-2024

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JSC370: Data Science II (Winter 2024), University of Toronto

Where and When

Weekly Course Schedule

Topics/Weekly Activities Due Dates
by 11:59 pm Fridays unless noted
Week 1
January 8 lecture pdf
January 10 lab		 Introduction to Data Science tools: R, markdown Lab 1
Week 2
January 15 lecture pdf
January 17 lab
Version Control & Reproducible Research, Git		 Lab 2
Week 3
January 22 lecture pdf
January 24 lab (sample solution)		 Exploratory Data Analysis Lab 3
Week 4
January 29 lecture pdf
January 31 lab (sample solution)		 Data visualization HW1, Lab 4
Week 5
February 5 lecture pdf
February 7 lab (sample solution)		 Data cleaning and wrangling
ML 1 advanced regression
advanced regression solution		 Lab 5
Week 6
February 12 lecture pdf
February 14 lab (sample solution)		 Regular Expressions, Data scraping, using APIs HW2, Lab 6
Week 7
February 21		 Reading Week
Week 8
February 26 lecture
February 28 lab (sample solution)		 Text mining Lab 8
Week 9
March 4 lecture
March 6 lab (sample solution)		 High performance computing, cloud computing Midterm, Lab 9
Week 10
March 11 lecture
March 13 lab (sample solution, lab-b (optional) (sample solution)		 ML 2 (trees, rf, xgboost) Lab 10
Week 11
March 18 lecture
March 20 lab11 (sample solution)
Interactive visualization and effective data communication I		 HW3, Lab 11
Week 12
March 25 lecture
March 27 lab12		 Interactive visualization and effective data communication II Lab 12
Week 13
April 1 lecture
April 3		 Final Project Workshop HW4
Week 15
April 30		 Final Project, HW5

Grading Breakdown

Task % of Grade
Labs (including attendance) 10
Homework (5) 25
Midterm report 30
Final project 35

Resources

Markdown

Helpers and Templates

  • RMarkdown Cheatsheet An overview of Markdown and RMarkdown conventions.
  • RStudio Cheatsheets Other quick guides, including a more comprehensive RMarkdown reference and a information about using RStudio's IDE, and some of the main tools in R.

Guides

Tools

  • Apple's Developer Tools Unix toolchain. Install directly with xcode-select --install, or just try to use e.g. git from the terminal and have OS X prompt you to install the tools.
  • Homebrew package manager. A convenient way to install several of the tools here, including Emacs and Pandoc.
  • R. A platform for statistical computing.
  • knitr. Reproducible plain-text documents from within R.
  • Python and SciPy. Python is a general-purpose programming language increasingly used in data manipulation and analysis.
  • RStudio. An IDE for R. The most straightforward way to get into using R and RMarkdown.
  • TeX and LaTeX. A typesetting and document preparation system. You can write files in .tex format directly, but it is more useful to just have it available in the background for other tools to use. The MacTeX Distribution is the one to install for macOS.
  • Pandoc. Converts plain-text documents to and from a wide variety of formats. Can be installed with Homebrew. Be sure to also install pandoc-citeproc for processing citations and bibliographies, and pandoc-crossref for producing cross-references and labels.
  • Git. Version control system. Installs with Apple's Developer Tools, or get the latest version via Homebrew.
  • GNU Make. You tell make what the steps are to create the pieces of a document or program. As you edit and change the various pieces, it automatically figures out which pieces need to be updated and recompiled, and issues the commands to do that. See Karl Broman's Minimal Make for a short introduction. Make will be installed automatically with Apple's developer tools.
  • lintr and flycheck. Tools that nudge you to write neater code.

Other Applications and Services

  • Backblaze. Secure off-site backup.
  • GitHub. Host public Git repositories for free. Pay to host private ones. Also a source for publicly available code (e.g. R packages and utilities) written by other people.
  • Marked 2. Live HTML previewing of Markdown documents. Mac OS X only.
  • Sublime Text. Python-based text editor.
  • Zotero, Mendeley, and Papers are citation managers that incorporate PDF storage, annotation and other features. Zotero is free to use. Mendeley has a premium tier. Papers is a paid application after a trial period. I don't use these tools much, but that's not for any strong principled reason---mostly just intertia. If you use one and want to integrate with the material here, just make sure it can export to BibTeX/BibLaTeX files. Papers, which I've used most recently, can handily output citation keys in pandoc's format amongst several others.

Data

Many of these websites have API to download the data. We recommend you using APIs to get data.

Health and Biological data

Academic Publications and related

Other data

Social Networks