Course schedule

This schedule is tentative and may be adjusted at the discretion of the instructor. Check back for updates.

Week Theme Tuesday meeting Thursday meeting Section meeting
0 Module 0: Introductions NO CLASS Course orientation NO LAB
1 Module 0: Introductions

0.1 Lecture:

  • on research projects in(volving) data science

0.2 Activity:

  • collaboration using GitHub
 Software and technology overview
2 Module 0: Introductions

0.3 Lecture/discussion:

  • introducing class survey data

0.4 Activity:

  • exploratory and descriptive analysis
 tidyverse
3 Module 1: biomarkers

1.1 Discussion/lecture:

  • sharing results of survey data analysis;

  • introducing biomarker data

1.2 Lecture:

  • on prediction
 tidymodels
4 Module 1: biomarkers

1.3 Lecture:

  • on classification

1.4 Lecture/discussion:

  • on variable selection;

  • review published analysis of biomarker data

 classification
5 Module 2: web fraud

2.1 Lecture/discussion:

  • sharing analysis of soil temperature data;

  • introducing web fraud data

2.2 Lecture:

  • on text as data
 text processing
6 Module 2: web fraud

2.3 Lecture:

  • on multiclass classification

2.4 Activity:

  • measuring classification accuracy
 keras
7 Module 3: soil temperature NO CLASS (VETERANS DAY)

3.1 Discussion/lecture:

  • time series analysis

  • sharing results of biomarker analysis;

  • introducing soil temperature data

3.2 Lecture:
  • on time
8 Module 3: soil temperature

3.3 Lecture:

  • on space
 3.4 Discussion: results spatial analysis
9 Module 4: vignettes

4.1 Activity:

  • workshopping vignettes
 NO CLASS (THANKSGIVING HOLIDAY) NO LAB
10 Module 4: vignettes

4.2 Activity:

  • teaching exchange

4.3 Activity/discussion:

  • teaching exchange;

  • closing

 NO LAB