Stat GU4243/GR5243 Applied Data Science

Spring 2021 - Teaching Materials (Syllabus)

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

---

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

(starter codes)

Week 1 (Jan 13)

• Introduction to ADS
• Project 1 description
• Tutorial 1 R Notebook + Example: Repo | Knitted HTML R Notebook | Presentation + More Examples: Repo1
• A tutorial on GitHub

Week 2 (Jan 20)

• Recap on last week
• Overview of starter codes
• Submission and presentation for project 1
• Discussion and Q&A

Week 3 (Jan 27)

• Project 1 presentations.

Finished student projects

---

Shortcuts: Project 1 | Project 3 | Project 4

Project cycle 2: Shiny App Development

(starter codes)

Week 3 (Jan 27)

• Project 2 starts.
  • Check Piazza for your project team and GitHub join link on Friday.
  • 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 3)

• Spatial data visualization
• Tutorial on project 2 - Introduction to shiny app (app)
• Shiny Tutorial (zipped folder) (online link)
• Shiny Examples from previous semesters (Example 1: Online, Repo; Example 2: Online, Repo)
• A note on contribution
• Discussion and Q&A

Week 5 (Feb 10)

• Tutorial on SQL in R(zipped folder)
• Tutorial on RShiny Deployment in GCP
• Tutorial on giving presentations
• Brainstorm or Discussion on project 2

Week 6 (Feb 17)

• Project 2 presentations

Finished student projects

---

Shortcuts: Project 1 | Project 2 | Project 4

Project cycle 3: Predictive Modeling

(starter codes)

Week 6 (Feb 17)

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

Week 7 (Feb 24)

• Recap on project 3 requirements and starter codes.
• Tutorials + Q&A
  • Tutorials: Basic Image Analysis (zipped folder) + Fiducial Detection
  • Tutorial on gradient boosting machines (GBM) [Tutorial Notes]
    • A shiny app on GBM [R codes]
  • Overview on Imbalanced Classification

Spring Break

Week 8 (Mar 10)

• Overview on predictive modeling
• Project submission checklist (on piazza)
• Discussion

Week 9 (Mar 17)

• Project 3 submission and presentations

Finished student projects

---

Shortcuts: Project 1 | Project 2 | Project 3

Project cycle 4: Algorithm implementation and evaluation

(starter codes)

Week 9 (Mar 17)

• Introduction to Project 4

Weeks 10 (Mar 24)

• Recap on project 4 requirements.
• Overview of Causal Inference
• Overview of the Methods from the reference papers.
• Method assignment

Weeks 11 (Mar 31)

• Q&A
• Team Meeting

Weeks 12 (Apr 7)

• Project 4 presentations

Finished student projects

---

Project cycle 5:

Weeks 12 (Apr 7)

• Project 5 discussions
• Project 3 Summary

Week 13 (Apr 14)

• Project 5 presentations

Finished student projects

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