Data Science & Analytics Topics
Statistical analysis, data analytics, big data technologies, and data visualization. Covers statistical methods, exploratory analysis, and data storytelling.
Optimization and Operations Research Methods
Prescriptive analytics: formulating decisions as optimization problems — linear and integer programming, constraint-based modeling, objective functions, and trade-offs between optimality and tractability. Applied to allocation, scheduling, routing, pricing, and supply/demand problems.
Metrics and KPI Design
Defining, selecting, and monitoring the metrics that measure a business or product. Covers north-star and supporting metrics, guardrails, metric decomposition, segmentation, and operational monitoring and alerting. Emphasizes choosing metrics that are actionable and hard to game.
Estimation and Quantitative Reasoning
Producing defensible numeric estimates with limited data. Covers market sizing, back-of-the-envelope estimation, structuring assumptions, and sanity-checking magnitudes. Emphasizes transparent reasoning and reasonable approximation over false precision.