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Course site for Computing for Information Science (INFO 5940)
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Updated schedule of topics for info sci course #351

Closed bensoltoff closed 1 year ago

bensoltoff commented 2 years ago

Current schedule

  1. Intro/grammar of graphics
  2. Data transformation/EDA
  3. Data wrangling (tidy data/relational data and factors)
  4. Core programming concepts (pipes and functions/vectors and iteration)
  5. Debugging/intro to R Markdown
  6. Reproducible workflows/reprex and Git
  7. Machine learning
  8. Getting data from the web (API/web scraping)
  9. Text analysis (fundamentals and sentiment analysis/supervised and unsupervised learning)
bensoltoff commented 2 years ago

Cornell runs on 16 week semester. Meet twice a week = 32 class meetings. In the fall there are 4 days when class is canceled (Labor Day, Fall Break, Thanksgiving Break, last week of classes ends on a Monday so no Wednesday meetings). Total of 28 instructional days, 10 more than what I have now.

Class periods missed

Revised schedule

  1. Intro to the course
  2. Grammar of graphics and ggplot2
  3. Data transformation
  4. Exploratory data analysis
  5. No class (Labor Day)
  6. Data wrangling - tidy data
  7. Data wrangling - relational data and factors
  8. Core programming concepts - pipes and functions
  9. Core programming concepts - vectors and iteration
  10. Core programming concepts - tidyeval
  11. Debugging
  12. Reprex and asking for help
  13. Reproducible documents - Quarto and basic documents
  14. Reproducible documents - extensions to slide decks, websites, deploying with Netlify
  15. No class (Fall Break)
  16. Reproducible workflows
  17. Intro to Git
  18. Extended Git workflows
  19. Machine learning - intro to ML, build models with parsnip, resample data with rsample
  20. Machine learning - build better training data with recipes, create workflows with workflows
  21. Machine learning - hyperparameter tuning with tune
  22. Getting data from the web - API
  23. Getting data from the web - web scraping
  24. Geospatial viz - raster maps
  25. Geospatial viz - vector graphics and sf
  26. Text analysis - fundamentals and sentiment analysis
  27. Text analysis - supervised and unsupervised learning
  28. No class (Thanksgiving)
  29. Shiny apps - 1
  30. Shiny apps - 2
  31. Improved data communication
  32. No class (pre-exam period)