Chenhao ZhouRutgers Business School

Teaching

Open Projects

The projects behind these materials, and how to join one

Two projects are open to students this term, both on public data: what the work is, what you need before starting, and where it leads. A four-week preparation sequence uses only the materials on this page.

2 open projects · 1–2 hours a week to start · co-authorship from 4 hours a week
See the tracks →

Interactive Online Courses

Full Course

Machine Learning: From Business Analytics to Code

A comprehensive journey from business thinking to ML implementation. Covers regression, classification, trees, ensembles, neural networks, and NLP with interactive Python labs.
11 Modules · 3 Capstone Projects · Real-World Case Studies
Launch Course →
Full Course

ML Frameworks & Applied Analytics

Building scalable ML systems from architecture to deployment. Covers pipeline engineering, MLOps, model serving, and production-ready frameworks.
4 Core Frameworks · Pipeline Engineering · MLOps
Launch Course →
Full Course

Supply Chain Finance

From working capital fundamentals to stochastic pricing models. Trade credit, inventory finance, futures hedging, FinTech platforms, and Black-Scholes derivations.
6 Chapters · Senior UG / Master · Applied + Quantitative
Launch Course →

Coding Reference Guides (Online Books)

10 Chapters

Python for Data Science & Analytics

From first script to end-to-end data pipelines. NumPy, Pandas, Matplotlib, scikit-learn, APIs, and statistical analysis with statsmodels.
Beginner to Intermediate · Business Analytics Focus
Open Book →
10 Chapters

Stata for Econometrics & Research

Do-files to publication-ready results. OLS, panel data, IV, DID, RDD, matching, GMM, SFA, and Heckman with diagnostic protocols.
Graduate Level · Empirical Research Focus
Open Book →
10 Chapters

R for Statistical Computing

Tidyverse workflows, ggplot2 visualization, linear and generalized models, tidymodels ML, and reproducible research with R Markdown and Quarto.
Graduate Level · Statistical Analysis Focus
Open Book →
10 Chapters

SQL for Data Analytics

Relational databases from SELECT to window functions. Joins, CTEs, aggregation, database design, query optimization, and end-to-end analytics pipelines.
All Levels · Business Intelligence Focus
Open Book →

Interactive Simulations & Demos

🚢

Port Operations

4 variance strategies: throughput, cost, wait time, balanced

Interactive
⏳

Queueing System (M/M/c)

Exponential, uniform, normal, Erlang, triangular

Interactive
🏥

Infusion Center Scheduling

AnyLogic cloud model for oncology outpatient operations

Interactive
📰

Newsvendor Model

Critical ratio, overage/underage costs, optimal order quantity

Interactive
🚛

Vehicle Routing (TSP)

Nearest Neighbor, 2-Opt, Insertion, Christofides

Interactive
📍

Facility Location

Capacitated MIP with coverage and cost trade-offs

Interactive

Supply Chain Finance Simulations

💰

Cash Conversion Cycle

DIO, DSO, DPO and working capital impact

Interactive
🔄

Reverse Factoring

Buyer-led SCF program cost comparison

Interactive
⚡

Dynamic Discounting

Early payment optimization, APR returns

Interactive
📊

Working Capital

KPI tracking, trend visualization

Interactive
📈

Trade Credit NPV

Payment timing strategies and firm value

Interactive
📋

Factoring Analysis

Recourse vs. non-recourse, fees, advance rates

Interactive
🎯

Portfolio Optimization

Mean-variance, efficient frontier

Interactive
⚠️

VaR & Risk Metrics

Historical, parametric, Monte Carlo VaR/CVaR

Interactive
🎲

Monte Carlo Simulation

Stochastic profit simulation, confidence intervals

Interactive
🏦

Credit Scoring

Logistic regression, ROC curves, default prediction

Interactive
📦

EOQ Demo

Holding costs, ordering costs, total cost curves

Interactive

Handbooks & Student Guides — Authored by Chenhao Zhou

DA

Data-Driven Analysis

EDA, correlation vs. causation, feature engineering
ML

ML for Business Analytics

Predictive modeling, data-driven decisions (2026)
SC

Supply Chain Finance & Operations

CCC, discounting, reverse factoring, Monte Carlo
CI

Endogeneity & Causal Inference

IV, DID, RDD, synthetic control (2026)
AI

Teaching with Claude AI

Content generation, formatting workflows
01

Online Learning Resources

Curated: Coursera, edX, DataCamp
02

AI-Powered Coding

Claude Desktop, Code, MCP integrations
03

Professional Digital Presence

Website, GitHub, online branding
Demand Planning & Fulfillment

Peer Evaluation

For current submission instructions, please refer to Canvas.