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Practice and Application of Data Science

DSC 259R

Sam Lau
he/him

lau@ucsd.edu

Lecture(s): TuTh 9:30-10:50AM (A00), 11:00AM-12:20PM (B00) in Cognitive Science 002

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Lectures

LEC 1

Introduction, Data Science Lifecycle

Ch. 1

LEC 2

DataFrame Fundamentals

🎥 | Ch. 6, 6.1

LEC 3

Ch. 6.2

LEC 4

Simpson's Paradox, Joining, Transforming

Ch. 6.3-6.5

LEC 5

Exploring and Cleaning Data

Ch. 9 and 10

LEC 6

Hypothesis and Permutation Testing

Pre-lecture review, Ch. 17

LEC 7

Missingness Mechanisms

Fast Permutation Tests, A1, A2

LEC 8

DSP 6.3-6.5

LEC 9

Ch. 14.2-14.4

LEC 10

Ch. 14.2-14.4

LEC 11

Regular Expressions

Ch. 13

LEC 12

Text Features

Ch. 13.4

LEC 13

Linear Regression

Ch. 15.0-15.6

LEC 14

Feature Engineering

Ch. 15.7-15.9

LEC 15

Standardization, Multicollinearity, and Generalization

Ch. 16, 17.6

LEC 16

Hyperparameters, Cross-Validation, and Decision Trees

Ch. 16

LEC 17

Decision Trees and Random Forests

A1

LEC 18

Classifier Evaluation and Model Fairness

Ch. 16

LEC 19

Model Fairness, Review, Conclusion

Ch. 19.5