Stat GR5243 Applied Data Science

Fall 2018 - Teaching Materials (Syllabus)

Shortcuts: Project 1 | Project 2 | Project 3 | Project 4

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

(starter codes)

Week 1 (Sep 5/6)

• Introduction to ADS
• Project 1 description
• Tutorial 1 R Notebook + Example
• A tutorial on GitHub

Week 2 (Sep 12/13)

• An example R notebook on presidential speeches
  • (zipped folder)
  • (known running issues&solutions, prepared by Yang Yang @jokerkeny)
• Overview of starter codes
• Data Story Examples: Example 1 (repo), Example 2 (repo).
• Discussion and Q&A

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Shortcuts: Project 1 | Project 3 | Project 4

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. ======= (starter codes)

Week 3 (Sep 19/20)

• Project 1 presentations.
• Project 2 starts.
  • A short tutorial In-class presentation
  • Check Piazza for your project team and GitHub join link.

origin/master + 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)

• Spatial data visualization
• Tutorial on project 2 - Introduction to shiny app (app)
• Shiny Tutorial (zipped folder) (online link) + example
• Shiny Example from 2018 Spring (link)
• Discussion and Q&A

Week 5 (Oct 3/4)

• Feebback on project 1
• Tutorial on giving presentations
• Brainstorm on project 2

Week 6 (Oct 10/11)

• Project 2 presentations

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Shortcuts: Project 1 | Project 2 | Project 4

Project cycle 3: Predictive Modeling

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 + the project description, + an example project

• [Intro to Project 3]
• [Example main.Rmd]

Week 7 (Oct 17/18)

• Tutorials + Q&A

Week 8 (Oct 24/25)

• Overview on predictive modeling
• Tutorials + Discussion

Week 9 (Oct 31/Nov 1)

• Project 3 presentations

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Shortcuts: Project 1 | Project 2 | Project 3

Project cycle 4: Algorithm implementation and evaluation

Week 9 (Oct 31/Nov 1)

• Introduction to Project 4

Week 10 (Nov 7/8)

• Overview of the reference papers.
• Tutorials + Discussion

Week 11 (Nov 14/15)

• Q&A on Algorithms
• Team Meeting

Thanksgiving break

Week 12 (Nov 28/29)

• Project 4 presentations
• Project 5 discussions

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Project cycle 5:

Week 13 (Dec 5/6)

• Project 5 Presentations

Shortcuts: Project 1 | Project 2 | Project 3 | Project 4