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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 GR4243/5243 Applied Data Science

Spring 2019 - Teaching Materials (Syllabus)


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

(starter codes)

Week 1 (Jan 23)

Week 2 (Jan 30)


Project cycle 2: Shiny App Development

(starter codes)

Week 3 (Feb 6)

  • 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 (Feb 13)

Week 5 (Feb 20)

Week 6 (Feb 27)

  • Project 2 presentations

Project cycle 3: Predictive Modeling

(starter codes)

Week 6 (Feb 27)

  • 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 (Mar 6)

Week 8 (Mar 13)

Spring break

Week 9 (Mar 27)

  • Project 3 submission and presentations

Project cycle 4: Algorithm implementation and evaluation

Week 9 (Mar 27)

Weeks 10 & 11 (Apr 3 & 10)

  • Q&A on Algorithms
  • Team Meeting

Week 12 (Apr 17)

  • Project 4 presentations
  • Project 5 discussions

Project cycle 5:

Week 13 (Apr 24)


Project cycle 5:

Week 14 (May 1)

  • 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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