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Lecture Notes
(see Syllabus for overview of course)
- Lecture 1, 2021-01-12: intro to course
- Lecture 2, 2021-01-19: setting the stakes
- Lecture 3, 2021-01-26: risk and social physics
- Lecture 4, 2021-02-02: statecraft and quantitative racism
- Lecture 5, 2021-02-09: intelligence, causality, and policy
- Lecture 6, 2021-02-16: data gets real: mathematical baptism
- Lecture 7, 2021-02-23: WWII, dawn of digital computation
- Lecture 8, 2021-03-09: birth and death of AI
- Lecture 9, 2021-03-16: big data, old school (1958-1980)
- Lecture 11, 2021-03-23: AI2.0
- Lecture 10, 2021-03-30: data science, 1962-2017
- Lecture 12, 2021-04-06: ethics
- Lecture 13, 2021-04-13: present problems: attention economy+VC=dumpsterfire
- Lecture 14, 2021-04-15: future solutions
Lab Notebooks (in Colab)
- Lab 1 python basics; "getting" data
- Lab 2 EDA with data about people (police stats)
- Lab 3 1830s stats; GPAs; BMI; Arbuthnot, 1620-1720's data
- Lab 4 Galton, eugenics
- Lab 5 Yule, Snow, Spearman, Simpson
- Lab 6 p-hacking
- Lab 7 statistical codebreaking
- Lab 8 Shannon, Eliza, AI1.0; perceptron
- Lab 9 Memex; SQL; reidentification; movies
- Lab 10 machine learning
- Lab 11 technical privacies; gerrymandering, see also:
- Lab 12 ethics fairness ; admissions
- Lab 13 lecture on power (little lab participation)