Data Science & Analytics Topics
Statistical analysis, data analytics, big data technologies, and data visualization. Covers statistical methods, exploratory analysis, and data storytelling.
SQL for Data Analysis
Writing SQL to answer analytical and business questions. Covers filtering, joins, grouping and aggregation, subqueries, CTEs, and translating an ambiguous request into a correct query. Includes spreadsheet-to-SQL fluency for everyday analyst workflows.
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.