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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).

HTML 99.96% R 0.03% Jupyter Notebook 0.01% CSS 0.01% JavaScript 0.01% TeX 0.01%

ads_teaching's Introduction

Stat GR4243/5243 Applied Data Science

Fall 2019 - Teaching Materials (Syllabus)


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

(starter codes)

Week 1 (Sep 4/5)

Week 2 (Sep 11/12)

Week 3 (Sep 18/19)

  • Project 1 presentations.

Project cycle 2: Shiny App Development

(starter codes)

Week 3 (Sep 18/19)

  • 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 25/26)

Week 5 (Oct 2/3)

Week 6 (Oct 9/10)

  • Project 2 presentations

Project cycle 3: Predictive Modeling

(starter codes)

Week 6 (Oct 9/10)

  • 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 16/17)

Week 8 (Oct 23/24)

  • Project submission checklist
  • Discussion

Week 9 (Oct 30/Nov 1)

  • Project 3 submission and presentations

Project cycle 4: Algorithm implementation and evaluation

Week 9 (Oct 30/Nov 1)

Weeks 10 (Nov 6/7)

Weeks 11 (Nov 13/14)

Weeks 12 (Nov 20/21)

  • Project 4 presentations

Project cycle 5:

Weeks 12 (Nov 20/21)

  • Project 5 discussions

Thanksgiving Break

Week 13 (Dec 4/5)

  • Project 5 presentations

ads_teaching's People

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