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Teaching repo for Applied Data Science @ Columbia, a project-based course for data science skills (statistical thinking, machine learning, data engineering, team work, presentation, endurance of frustration, etc).

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Stat GU4243/G5243 Applied Data Science

Fall 2017 - Teaching Materials (Syllabus)


Project cycle 1: (Individual) R notebook on presidential addresses

(starter codes)

Week 1 (1/20)

Week 2 (1/27)

Week 3 (2/3)

  • Project 1 presentations

Project cycle 2: shiny app development

(starter codes)

Week 3 (2/3)

  • Project 2 starts.
    • Check Piazza for your project team and GitHub join link.
    • After you join project 2, you can clone your team's GitHub repo to your local computer.
    • You can find in the starter codes
      • the project description,
      • an example toy shiny app
      • a short tutorial to get you started.

Week 4 (2/10)

Week 5 (2/17)

Week 6 (2/24)

  • Project 2 presentations

Project cycle 3: predictive modeling

(starter codes)

Week 6 (2/24)

  • Project 3 starts.
    • Check Piazza for your project team and GitHub join link.
    • After you join project 3, you can clone your team's GitHub repo to your local computer.
    • You can find in the starter codes
      • the project description,
      • an example project
  • Intro to Project 3
  • Example main.Rmd (pdf)

Week 7 (3/3)

Week 8 (3/10)

spring break

Week 9 (3/24)

  • Project 3 presentations

Project cycle 4: Algorithm implementation and evaluation

(starter codes)

Week 10 (3/31)

Week 11 (4/7)

  • Q&A on algorithms
  • Team meetings

Week 12 (4/14)

  • Project 4 presentations

Project cycle 5: free topic

Week 13 (4/21)

Week 14 (4/28)

  • Project 5 Presentations

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Teaching repo for Applied Data Science @ Columbia, a project-based course for data science skills (statistical thinking, machine learning, data engineering, team work, presentation, endurance of frustration, etc).

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