INFO 2951: Introduction to Data Science with R

Modified

March 14, 2025

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 Jan 21 Lec 1 Welcome to INFO 2951 hw-00
Thu Jan 23 Lec 2 Meet the toolkit
Fri Jan 24 Lab Hello data science! lab-00
2 Tue Jan 28 Lec 3 Grammar of graphics
Thu Jan 30 Lec 4 Visualizing various types of data
Fri Jan 31 Lab Data visualization lab-01 + hw-01
3 Tue Feb 4 Lec 5 Grammar of data wrangling
Thu Feb 6 Lec 6 Working with relational data
Fri Feb 7 Lab Data wrangling lab-02 + hw-02
4 Tue Feb 11 Lec 7 Tidying data
Thu Feb 13 Lec 8 Data types and classes
Fri Feb 14 Lab Git workflows (basics + merge conflicts) lab-git
5 Tue Feb 18
No class (February Break)
Thu Feb 20 Lec 9 Importing and recoding data
Fri Feb 21 Lab Git workflows (branches + PRs) lab-03 + hw-03
6 Tue Feb 25 Lec 10 Databases + SQL
Thu Feb 27 Lec 11 Getting data from the web: Scraping
Fri Feb 28 Lab Develop project proposals proj-proposal + hw-04
7 Tue Mar 4 Lec 12 Functions
Thu Mar 6 Lec 13 Iteration
Fri Mar 7 Lab Functions + iteration lab-04 + hw-05
8 Tue Mar 11 Lec 14 Getting data from the web: APIs
Thu Mar 13 Lec 15 Rectangling data
Fri Mar 14 Lab Review for the prelim ???
9 Tue Mar 18 Lec 16 Hypothesis testing with randomization exam-01 (evening)
Thu Mar 20 Lec 17 Quantifying uncertainty with the bootstrap
Fri Mar 21 Lab Develop project exploration proj-explore + hw-06
10 Tue Mar 25 Lec 18 Linear regression with a single predictor
Thu Mar 27 Lec 19 Linear regression with multiple predictors
Fri Mar 28 Lab Statistical inference
11 Tue Apr 1
No class (Spring Break)
Thu Apr 3
No class (Spring Break)
Fri Apr 4
No class (Spring Break)
12 Tue Apr 8 Lec 20 Models for discrete outcomes
Thu Apr 10 Lec 21 Reproducible reporting with Quarto
Fri Apr 11 Lab
lab-05 + hw-07
13 Tue Apr 15 Lec 22 Introduction to machine learning
Thu Apr 17 Lec 23 Build better training data
Fri Apr 18 Lab Work on project drafts proj-draft
14 Tue Apr 22 Lec 24 Tree-based inference and hyperparameter optimization
Thu Apr 24 Lec 25 An introduction to LLMs
Fri Apr 25 Lab Project peer reviews proj-peer + hw-08
15 Tue Apr 29 Lec 26 Text analysis: fundamentals and sentiment analysis
Thu May 1 Lec 27 Text analysis: supervised text classification
Fri May 2 Lab Project presentations proj-present + hw-09
16 Tue May 6 Lec 28 Wrap-up: Where to go from here proj-final
NA

Final exam exam-02