ISOM 835: Predictive Analytics
& Machine Learning
Every business question about the future is a prediction problem. Learn to build the models that answer it — in Python, on real data, with the judgment to know when to trust them.
Mondays 5:00–7:30 PM • Every week: a business question, a dataset, a model you build yourself.
A guided course that runs in your browser — read, run, get graded — then Prof. Arslan's modules for depth.
Setup in eleven minutes, how each week works, the five habits.
The whole course on one page: templates, formulas, checklists.
Eight datasets with no-login loaders and the trap in each one.
Drag the model-complexity slider and watch training error fall while test error turns back up — the bias–variance trade-off as a living picture.
Nine Modules, Thirteen Mondays
From your first churn model to gradient boosting, forecasting, and LLM features — one prediction toolkit, built module by module.
Foundations
The prediction lifecycle — and your first model, end to end. Sep 14Data & Features
Wrangling, exploration, and leak-proof feature pipelines. Sep 21 · Sep 28Data Wrangling & EDA for Prediction
Real data arrives in eight tables, three date formats, and a thousand blanks. pandas joins, groupbys, and datetime features on Olist e-commerce — and how to spot the leak that makes a model look brilliant and ship useless
Feature Engineering & Leak-Proof Pipelines
Encoders, scalers, imputers, and the scikit-learn Pipeline — the machinery that turns a messy table into a model input without ever peeking at the test set
Classification & Decisions
Predicting yes/no — then turning probabilities into profitable decisions. Oct 5 · Oct 19Classification: Predicting Yes/No
Logistic regression as odds, kNN and Naive Bayes as contrasts, the confusion matrix in depth, precision vs. recall, ROC vs. PR — on 30,000 credit-card customers, 22% of whom default
From Scores to Decisions: Thresholds, Costs & Calibration
A model produces a probability; a business produces a decision. Expected value, profit curves, tuned thresholds, calibration, lift and gain — and the launch of the Midterm Model Competition
Regression
Predicting numbers: linear models, regularization, and what a residual is telling you. Oct 26Trees & Ensembles
Random forests, gradient boosting, and the tabular frontier. Nov 2 · Nov 9Decision Trees & Random Forests
How a tree asks questions, why it memorizes, and how averaging hundreds of decorrelated trees turns a fragile model into the most reliable workhorse in tabular ML
Gradient Boosting & the Tabular Frontier
Fit the residuals, again and again: HistGradientBoosting, LightGBM, XGBoost, early stopping — and the tabular foundation models that, since 2025, beat tuned boosting on small data with zero tuning. Plus: the competition reveal
Evaluation & Optimization
Tuning, explaining, and trusting a model. Nov 16Unsupervised Learning
Segments, structure, and anomalies — learning without labels. Nov 23Time & Text
Forecasting, neural networks, embeddings, and LLMs as features. Nov 30 · Dec 7Forecasting: Time Series With ML & Foundation Models
Why random splits lie when time matters, lag and rolling features that turn forecasting into regression, classical baselines you must beat, and the zero-shot foundation models that changed the field in 2025
Neural Networks, Embeddings & LLMs as Features
A multilayer perceptron on tabular data (and why it usually loses to boosting), text as features — TF-IDF, sentence embeddings, zero-shot LLM labels — and the AI-assisted analyst's workflow: generate, verify, own
Finale
Ship it — and present your prediction story. Dec 14No class Mon Oct 12 (October Break) · Session 13 meets in the exam-week slot, Mon Dec 14
Meet Your Professor
Prof. Hasan Arslan, PhD
Chief AI Officer, Sawyer Business School · Associate Professor of Information Systems & Operations Management
Leads AI integration across the Sawyer Business School. Specializes in AI-powered business solutions, prescriptive and predictive analytics, and operations management. Creator of the SAIL Framework and recipient of the 2025 Eduventures Innovation Award. PhD from MIT.