Shuangjie Zhang | University of Texas at Austin

Teaching

I teach applied, computing-first statistics — students spend class time writing code against real data rather than watching derivations.

SDS 322E Spring 2026 · UT Austin

Elements of Data Science

Data science tools and workflow: data wrangling, exploratory analysis and visualization, Markdown and reproducible reporting, simulation-based inference, and classification. R is emphasized; Python is introduced.

Role Lecturer

Format 3 lectures + 1 lab weekly

Level Undergraduate

Language R, with Python intro

Full syllabus (PDF) RStudio / Tidyverse Git-based collaboration

Unit 1

Analytic Thinking and Visualization

Tidy data, summarizing in one and two dimensions, basic visualization, and R Markdown notebooks.

Unit 2

Data Wrangling

ggplot2, dplyr, and tidyr: reshaping, joining and merging, missing data, regular expressions and text.

Unit 3

Modeling and Analysis

Clustering and PCA, linear and logistic regression, tree-based methods, prediction metrics, cross-validation.

Unit 4

Expanding Horizons

Causal inference, propensity scores, and building dashboards.

By the end of the course, students can write R code and build analyses in R Markdown; use Tidyverse tools to wrangle, clean, and visualize data; and fit supervised and unsupervised models to quantify relationships in high-dimensional data.

Previously

STAT 7 Statistical Methods for the Biological, Environmental, and Health Sciences UC Santa Cruz Winter 2024
STAT 132 Classical and Bayesian Inference UC Santa Cruz Winter 2023
STAT 131 Introduction to Probability Theory UC Santa Cruz Spring 2023, Fall 2023
STAT 5 Statistics UC Santa Cruz 6 quarters, 2019-2022
STA 601 Bayesian Methods and Modern Statistics Duke University Fall 2018

All roles above were as a Teaching Assistant.