Preface
STAT 4160: Data Science Productivity Tools
Preface
Introduction
1
Session 1 — Dev environment & Colab workflow
2
Session 2 — Git essentials & Git‑LFS
3
Session 3 — Quarto Reports (Python)
4
Session 4 — RStudio Quarto cameo + Report Hygiene
5
Session 5 — Unix/Shell Essentials for Data Work
6
Session 6 — Make/Automation + rsync + ssh/tmux (survey)
7
Session 7 — SQL I: SQLite Schemas & Joins
8
Session 8 — SQL II: Window Functions & `pandas.read_sql` Workflows
9
Session 9 — Cleaning, Joins, and Parquet
10
Rolling Windows, Resampling, and Leakage‑Safe Features
11
Session 11 — APIs with
requests
: Secrets, Retries, and Caching
12
Session 12 — HTML Scraping: Ethics & Resilience
13
Session 13
14
pre‑commit & GitHub Actions CI
15
Session 15 — Framing & Metrics (Rolling‑Origin Evaluation)
16
Session 16
17
Session 17 — Feature Timing, Biases & Leakage
18
Session 18 — Walk‑forward + Regime Analysi
19
Session 19 — Tensors, Datasets, Training Loop
20
Session 20 — Multi‑asset training (unified model
21
Session 21 — Attention & Tiny GPT on Toy Data
22
Session 22 — Adapting GPT to Time Series
23
Session 23 — Packaging & CLI (Typer)
24
Session 24 — Reproducibility audit & optional FastAPI
25
Session 25 — Poster + Abstract Workshop
26
Session 26 — In‑class Presentations & Continuation Pla
27
README.html
28
Lecture 5 (Pre) — Linux Basics
29
Summary
References
Table of contents
Preface
STAT 4160: Data Science Productivity Tools
Author
Yi Wang
Published
August 13, 2025
Preface
This is the lecture note for the course STAT 4160.
Introduction