Realistic AI engineering scenarios with reference solutions and problem-specific grading rubrics.
Capacity estimation · Key generation · Caching · Read-heavy systems
Drift Analysis · Root Cause Analysis · Covariate Shift · Concept Drift
Time Series · Hierarchical Forecasting · Backtesting · Intermittent Demand
Extreme Multi-Label · Hierarchical Classification · Active Learning · Human-in-the-Loop
Sensor Data · Survival Analysis · Rare Events · Edge Inference · Time Windows
Time Series · Unsupervised Learning · Streaming · Alerting · Seasonality
Candidate Generation · Ranking · Embeddings · Two-Tower Models · Cold Start
Vision Embeddings · ANN Search · Multimodal · Index Sharding · CLIP
Pipelines · Reproducibility · Experiment Tracking · Data Versioning · Orchestration
Data Quality · Skew Detection · Lineage · Freshness SLAs · Root Cause
Drift Detection · Delayed Labels · Alerting · Segment Analysis · Observability
Skew Debugging · Feature Pipelines · Data Leakage · Root Cause Analysis
Imbalanced Data · Threshold Tuning · Error Analysis · Precision-Recall Tradeoff
Incident Response · Root Cause Analysis · Debugging · Systems Thinking
Model Serving · GPU Scheduling · Autoscaling · Canary Deploys · Multi-tenancy
Ranking · Fan-out · Multi-Objective Optimization · Freshness · Feedback Loops
Streaming · Imbalanced Data · Feature Store · Low Latency · Adversarial ML
Learning to Rank · BM25 · Query Understanding · Click Models · Position Bias
CTR Prediction · Auctions · Calibration · Delayed Feedback · Budget Pacing
Feature Store · Point-in-Time Correctness · Streaming · Data Engineering
CI/CD · Canary Analysis · Shadow Deploys · Rollback · Automated Promotion