Detecting Fraudulent Sales Transactions
Build an audit queue from noisy sales records with scarce labels. Best if you already know the modeling workflow.
Explore the project Advanced practice with scarce labels.Projects
Messy datasets. Real business decisions. Choose a starting point that matches your experience.
Free Shipping Threshold Experiment
Clean an experiment export, compare outcomes, and recommend whether to change the shipping threshold.
View project & prerequisites Start here after Python and experimentation.Build your experience
Explore all nine projects
Download the data, work the brief end to end, and deliver your analysis the way you would on the job.
01Advanced
Machine LearningDetecting Fraudulent Sales Transactions
Detect fraud in 500k reported sales when only a few hundred are confirmed fraud and 96% were never inspected — a semi-supervised problem where the fraud signal must be engineered and the uninspected majority is used, not thrown away.
Data cleaningFeature engineering
02Intermediate
Experimentation & A/B TestingFree Shipping Threshold Experiment
Analyze a randomized experiment testing a lower free-shipping threshold and recommend whether to roll it out.
Experiment validity (SRM)Hypothesis testing
03Intermediate
Machine LearningInsurance Risk Tier Assignment
Assign each incoming auto policy application to one of six ordered risk tiers at quote time -- using only information that actually exists before the policy is bound.
Ordinal classificationLeakage auditing
04Advanced
Machine LearningSpare Parts Demand Forecast
Clean a messy, genuinely intermittent parts-demand history and build a MASE-evaluated forecast that beats a simple baseline.
Time-series data cleaningIntermittent-demand forecasting
05Advanced
Machine LearningAd Click & Conversion Prediction
Clean a raw ad-impression log and build models that predict clicks and conversions well enough -- and honestly enough -- to power a real feed-ranking system.
Class-imbalance handlingClassification metrics (ROC-AUC / PR-AUC)
06Advanced
Machine LearningMovie Recommendation Engine
Build a collaborative-filtering recommender for a streaming catalog from a sparse 1-5 ratings log -- predict ratings and rank personalized top-N picks -- evaluated with RMSE and Precision@N / Recall@N.
Collaborative filteringNeighborhood methods (user–user, item–item)
07Advanced
Machine LearningHierarchical Grocery Product Classification
Classify real store-shelf photos into a three-level product taxonomy -- department, product class, variety -- well enough to power a self-checkout that suggests the right produce button.
Transfer learning & fine-tuningHierarchical classification
08Advanced
AI EngineeringCustomer Support Resolution Agent
Build an LLM agent that reads a support ticket, looks the facts up with tools, applies the written policy, and picks the right action -- without believing a word the ticket says that it can check.
Tool design & function callingGrounding & hallucination control
09Advanced
Reinforcement LearningPerishable Inventory Replenishment
Train a reinforcement-learning agent to reorder a fast-spoiling grocery item each day -- batching against a flat per-delivery fee while avoiding both spoilage and stockouts -- and beat the store's daily base-stock rule.
Reinforcement learningMarkov decision processes