COGS108/Readings

A curated list of suggested reading materials.

Readings

A (work in progress) curated list of suggested reading materials relating to Data Science.

Note that tutorial materials, and readings related to specific topics are more likely to be listed in our Tutorials, and not necessarily copied here.

Articles

• 50 Years of Data Science, D Donoho
• Exploratory Data Analysis, JW Tukey
• Depth of Learning, M Buchanan
• Points of View: Storytelling, M Krzywinski & A Cairo
• Data Organization in Spreadsheets, K Broman & K Woo
• Good Enough Practices in Scientific Computing, G Wilson et al.

Writing Code / Programming Practices

• Programming Principles
  • https://www.makeuseof.com/tag/basic-programming-principles/
  • https://www.makeuseof.com/tag/weird-programming-principles/
• Software development skills for data scientists, Trey Causey (2015)

Blogs

• Better Explained
  • A good resource for accessible math explainers
• Simply Statistics
  • Covers statistics, data science, and AI
• What's the Big Data
  • Curates a lot of quick, interesting things on data science in general, largely industry focused
• Probability and Statistics for Data Science
  • "These notes were developed for the course Probability and Statistics for Data Science at the Center for Data Science in NYU."
• Datawrapper
  • A data-visualization blog chock full of great knowledge and examples

Textbooks

• Data Science from Scratch, Joel Grus
• Python Data Science Handbook, Jake VanderPlas

Journals

• Harvard Data Science Review
  • https://hdsr.mitpress.mit.edu/
• Distill
  • https://distill.pub/about/
• GigaScience
  • https://academic.oup.com/gigascience
• Journal of Open Source Software
  • https://joss.theoj.org/about
• Scientific Data
  • https://www.nature.com/sdata/