This page contains an outline of the topics, content, and assignments for the semester. Note that this schedule will be updated as the semester progresses and the timeline of topics and assignments might be updated throughout the semester.
week
dow
date
what
topic
prepare
slides
ae
ae_sa
hw
hw_sa
lab
lab_sa
exam
project
notes
1
Tue
Aug 27
Lec 1
Welcome to INFO 5001
Thu
Aug 29
Lec 2
Grammar of graphics
Fri
Aug 30
Lab
Hello data science!
lab-00
2
Tue
Sep 3
No class
Thu
Sep 5
Lec 3
Visualizing various types of data
Fri
Sep 6
Lab
Data visualization
lab-01 + hw-01
3
Tue
Sep 10
Lec 4
Grammar of data wrangling
Thu
Sep 12
Lec 5
Working with multiple data frames
Fri
Sep 13
Lab
Git workflows (basics + merge conflicts)
lab-git + hw-02
4
Tue
Sep 17
Lec 6
Tidying data
Thu
Sep 19
Lec 7
Data types and classes
Fri
Sep 20
Lab
Data tidying
lab-02
5
Tue
Sep 24
Lec 8
Importing and recoding data
Thu
Sep 26
Lec 9
Recoding data with columnwise operations
Fri
Sep 27
Lab
Git workflows (branches + PRs)
lab-03 + hw-03
6
Tue
Oct 1
Lec 10
Getting data from the web: Scraping
Thu
Oct 3
Lec 11
Functions
Fri
Oct 4
Lab
Develop project proposals
proj-proposal
7
Tue
Oct 8
Lec 12
Iteration
Thu
Oct 10
Lec 13
Getting data from the web: APIs
Fri
Oct 11
Lab
Functions + iteration
lab-04
8
Tue
Oct 15
No class (Fall Break)
Thu
Oct 17
Lec 14
Rectangling data
Fri
Oct 18
Lab
Develop project exploration
proj-explore + hw-04
9
Tue
Oct 22
Lec 15
Debugging tips + tools
Thu
Oct 24
Lec 16
Reproducible project-based workflows
Fri
Oct 25
Lab
No class (Exam 1)
exam-01
10
Tue
Oct 29
Lec 17
Customizing Quarto reports and presentations
Thu
Oct 31
Lec 18
Introduction to machine learning
Fri
Nov 1
Develop project draft
proj-draft
11
Tue
Nov 5
Lec 19
Build better training data
Thu
Nov 7
Lec 20
Tree-based inference and hyperparameter optimization
Fri
Nov 8
Lab 6
Implement machine learning workflows
lab05 + hw05
12
Tue
Nov 12
Lec 21
Text analysis: fundamentals and sentiment analysis