STATS 780

Data Science

Graduate

Fall 2026 · C01

Readings

eText Python Data Science Handbook - Lifetime Access Ed: 2
Vanderplas · 2 · Suggested
ISBN 9781098121181; 9781098121228
An Introduction To Statistical Learning: With Applications In Python
James · Required
ISBN 9783031387463

Fall 2026 · C01

Introduction to data science (data life cycle, reproducibility, Python ecosystem)
SQL and data management (joins, aggregate, relational databases, large datasets)
Data wrangling and visualization (visualization principals and dashboards (briefly)
Signal processing (signals, sampling, Fourier transform, filtering, wavelets, PCA, applications)
Trees and random forests
Boosting
Neural networks (perceptron, multilayer networks, backpropagation)
Neural networks in practice (overfitting, dropout, tuning)
Uncertainty quantification (bootstrap, prediction intervals, conformal prediction)
Interpretability and Generative AI (SHAP, feature importance, LLMs)

An Introduction to Statistical Learning with Applications in Pytho
James, G., Witten, D., Hastie, T., Tibshirani, R., & Taylor, J. · 2023 · 2 · Required
Springer
Python Data Science Handbook: Essential Tools for Working with Data.
VanderPlas, J. · 2016 · Required
O'Reilly Media, Inc.
An Introduction to Statistical Learning with Applications in Pytho Authors: James, G., Witten, D., Hastie, T., Tibshirani, R., & Taylor, J. Publisher: Springer Publication Date: 2023 Edition: 2
See source

Fall 2025 · C01

Etext The Elements Of Statistical Learning: Data Mining, Inference, And Prediction - Lifetime Access
Hastie · Required
ISBN 9780387848587; 9780387848570

Sources