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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 GR5243 Applied Data Science

Fall 2018 - Teaching Materials (Syllabus)


Project cycle 1: (Individual) R notebook for exploratory data analysis

(starter codes)

Week 1 (Sep 5/6)

Week 2 (Sep 12/13)

Finished student projects


Project cycle 2: Shiny App Development

(starter codes)

Week 3 (Sep 19/20)

  • Project 1 presentations.
  • 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 (Sep 26/27)

Week 5 (Oct 3/4)

Week 6 (Oct 10/11)

  • Project 2 presentations

Finished student projects


Project cycle 3: Predictive Modeling

(starter codes)

Week 6 (Oct 10/11)

  • 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

Week 7 (Oct 17/18)

Week 8 (Oct 24/25)

Week 9 (Oct 31/Nov 1)

  • Project 3 update
  • Q&A

Week 10 (Nov 7/8)

  • Project 3 submission and presentations

Project cycle 4: Algorithm implementation and evaluation

Week 10 (Nov 7/8)

Week 11 (Nov 14/15)

  • Q&A on Algorithms
  • Team Meeting

Thanksgiving break

Week 12 (Nov 28/29)

  • Project 4 presentations
  • Project 5 discussions

Project cycle 5:

Week 13 (Dec 5/6)

  • 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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