[ { "id": "ci-foundations", "title": "Causal Inference Foundations", "category": "Causal Inference", "level": "Beginner", "price": 249, "durationHours": 12, "shortDescription": "Draw causal diagrams, reason about confounding, and plan analyses with confidence.", "description": "This course builds intuition for causal inference with directed acyclic graphs (DAGs), backdoor criteria, and counterfactual thinking. You will practice identifying confounders, mediators, and colliders and design practical interventions.", "outcomes": ["Interpret DAGs for real decisions", "Select adjustment sets", "Plan robust analyses"], "tags": ["Analyst", "Product Manager", "DAGs", "Confounding"], "format": "Self-paced", "language": "English", "rating": 4.7 }, { "id": "bayes-intro", "title": "Bayesian Thinking for Decisions", "category": "Bayesian", "level": "Beginner", "price": 199, "durationHours": 10, "shortDescription": "Update beliefs, quantify uncertainty, and communicate probabilities clearly.", "description": "A gentle path into Bayesian reasoning using simple, intuitive examples. Learn priors, likelihoods, posteriors, and credible intervals with business applications.", "outcomes": ["Translate uncertainty into decisions", "Construct simple Bayesian models", "Explain credible intervals"], "tags": ["Analyst", "Leader", "Bayesian", "Probabilistic"], "format": "Self-paced", "language": "English", "rating": 4.6 }, { "id": "ab-testing", "title": "Experimentation & A/B Testing", "category": "Experiments", "level": "Intermediate", "price": 299, "durationHours": 14, "shortDescription": "Design, run, and analyze experiments with guardrails and power.", "description": "Cover hypotheses, power analysis, randomization, sequential testing, and guardrail metrics. Includes case studies on product and marketing experiments.", "outcomes": ["Design high-power tests", "Use guardrail metrics", "Avoid peeking pitfalls"], "tags": ["Data Scientist", "Product Manager", "Experiments", "Power"], "format": "Cohort", "language": "English", "rating": 4.8 }, { "id": "uplift-modeling", "title": "Uplift Modeling in Practice", "category": "Predictive", "level": "Advanced", "price": 349, "durationHours": 16, "shortDescription": "Target the persuadable using uplift and treatment effect models.", "description": "Learn theory and practice of uplift modeling, causal forests, and propensity methods to estimate heterogeneous treatment effects.", "outcomes": ["Estimate segment-level effects", "Evaluate uplift campaigns", "Avoid common biases"], "tags": ["Data Scientist", "Causal ML", "Marketing", "Uplift"], "format": "Cohort", "language": "English", "rating": 4.7 }, { "id": "dag-advanced", "title": "Advanced DAG Workflows", "category": "Causal Inference", "level": "Advanced", "price": 329, "durationHours": 12, "shortDescription": "From identification to estimation with real-world DAGs.", "description": "Move beyond basics into front-door paths, instrumental variables, and sensitivity analyses. Practice mapping complex systems and choosing estimators.", "outcomes": ["Apply front-door adjustment", "Use IV strategies", "Run sensitivity analyses"], "tags": ["Data Scientist", "DAGs", "IV", "Front-door"], "format": "Self-paced", "language": "English", "rating": 4.6 }, { "id": "guardrails", "title": "Guardrails for Product Metrics", "category": "Metrics", "level": "Intermediate", "price": 219, "durationHours": 8, "shortDescription": "Define metrics that protect user experience during change.", "description": "Establish trustworthy metrics with clear definitions, stability checks, and sensitivity to seasonality and mix shifts.", "outcomes": ["Design robust KPI suites", "Apply CUPED variance reduction", "Build metric reviews"], "tags": ["Product Manager", "Analyst", "Metrics", "CUPED"], "format": "Self-paced", "language": "English", "rating": 4.5 }, { "id": "uplift-eval", "title": "Evaluating Incrementality", "category": "Experiments", "level": "Intermediate", "price": 259, "durationHours": 9, "shortDescription": "Measure true causal lift in campaigns and product changes.", "description": "Separate correlation from causation with experiment-like evaluations, including geo tests and holdouts when randomization is limited.", "outcomes": ["Design holdout tests", "Use synthetic controls", "Report causal lift"], "tags": ["Marketing", "Analyst", "Causal ML", "Incrementality"], "format": "Self-paced", "language": "English", "rating": 4.6 }, { "id": "sql-decisions", "title": "SQL for Decision Scientists", "category": "Tooling", "level": "Beginner", "price": 149, "durationHours": 8, "shortDescription": "Write SQL that answers decision questions, not just reports.", "description": "Turn ambiguous questions into precise queries. Learn window functions, cohorts, and time-series joins for decision analysis.", "outcomes": ["Design cohort queries", "Use window functions", "Avoid time leakage"], "tags": ["Analyst", "SQL", "Tooling"], "format": "Self-paced", "language": "English", "rating": 4.4 }, { "id": "bayes-experiments", "title": "Bayesian Experiment Analysis", "category": "Bayesian", "level": "Advanced", "price": 329, "durationHours": 12, "shortDescription": "Analyze tests with priors, posteriors, and decision thresholds.", "description": "Apply Bayesian models to A/B tests, compute posterior probabilities of uplift, and set business decision thresholds.", "outcomes": ["Model posterior uplift", "Set decision rules", "Communicate uncertainty"], "tags": ["Data Scientist", "Experiments", "Bayesian"], "format": "Cohort", "language": "English", "rating": 4.7 }, { "id": "ethics-expts", "title": "Ethics in Experimentation", "category": "Governance", "level": "Beginner", "price": 129, "durationHours": 6, "shortDescription": "Build trust with ethical experiment practices and reviews.", "description": "Learn consent patterns, risk assessments, and equity considerations for product experiments and data projects.", "outcomes": ["Run ethics reviews", "Assess participant risk", "Document decisions"], "tags": ["Leader", "Governance", "Ethics"], "format": "Self-paced", "language": "English", "rating": 4.6 }, { "id": "forecast-decisions", "title": "Forecasting for Decisions", "category": "Predictive", "level": "Intermediate", "price": 249, "durationHours": 12, "shortDescription": "Practical forecasting for capacity and planning decisions.", "description": "Understand uncertainty ranges, seasonality, and scenario planning to support operations and product roadmaps.", "outcomes": ["Build baseline forecasts", "Quantify uncertainty bands", "Communicate risks"], "tags": ["Analyst", "Leader", "Forecasting"], "format": "Self-paced", "language": "English", "rating": 4.5 }, { "id": "decision-framing", "title": "Decision Framing & Narratives", "category": "Frameworks", "level": "Beginner", "price": 139, "durationHours": 7, "shortDescription": "Structured prompts that turn analysis into action.", "description": "Use decision briefs, alternatives, and trade-off matrices to guide stakeholders toward principled choices.", "outcomes": ["Create decision briefs", "Frame alternatives clearly", "Align stakeholders"], "tags": ["Product Manager", "Leader", "Communication"], "format": "Self-paced", "language": "English", "rating": 4.4 }, { "id": "uplift-design", "title": "Designing Geo Experiments", "category": "Experiments", "level": "Advanced", "price": 339, "durationHours": 14, "shortDescription": "Geo holdouts and synthetic controls for large-scale changes.", "description": "Plan geo experiments with matched markets, spillover checks, and robust inference techniques.", "outcomes": ["Match comparable markets", "Check spillover", "Estimate causal impact"], "tags": ["Marketing", "Experiments", "Geo"], "format": "Cohort", "language": "English", "rating": 4.7 }, { "id": "causal-ml", "title": "Causal ML Essentials", "category": "Causal Inference", "level": "Intermediate", "price": 299, "durationHours": 12, "shortDescription": "From propensity scores to causal forests.", "description": "Bridge classical causal inference with machine learning techniques to estimate treatment effects from observational data.", "outcomes": ["Propensity scoring", "Causal trees/forests", "Model evaluation"], "tags": ["Data Scientist", "Causal ML", "Observational"], "format": "Self-paced", "language": "English", "rating": 4.6 }, { "id": "risk-communication", "title": "Risk Communication for Leaders", "category": "Frameworks", "level": "Intermediate", "price": 199, "durationHours": 8, "shortDescription": "Talk uncertainty clearly without alarm or oversimplification.", "description": "Learn to present risk ranges, scenarios, and trade-offs in executive-friendly ways.", "outcomes": ["Design scenario briefs", "Use risk ranges", "Earn stakeholder trust"], "tags": ["Leader", "Communication", "Strategy"], "format": "Self-paced", "language": "English", "rating": 4.5 }, { "id": "power-analysis", "title": "Power Analysis in Practice", "category": "Experiments", "level": "Intermediate", "price": 219, "durationHours": 9, "shortDescription": "Size tests responsibly and avoid false confidence.", "description": "Compute sample sizes, consider variance, and design sequential tests with stopping boundaries.", "outcomes": ["Compute sample size", "Balance power vs. speed", "Use sequential methods"], "tags": ["Analyst", "Experiments", "Power"], "format": "Self-paced", "language": "English", "rating": 4.6 }, { "id": "measurement", "title": "Measurement for Product Analytics", "category": "Metrics", "level": "Beginner", "price": 159, "durationHours": 8, "shortDescription": "Measure what matters with reliable, interpretable metrics.", "description": "Define, validate, and maintain metrics that reflect user experience and business value.", "outcomes": ["Define clear metrics", "Check reliability", "Avoid proxy traps"], "tags": ["Product Manager", "Analyst", "Metrics"], "format": "Self-paced", "language": "English", "rating": 4.4 }, { "id": "confounding-lab", "title": "Confounding & Bias Lab", "category": "Causal Inference", "level": "Intermediate", "price": 239, "durationHours": 10, "shortDescription": "Hands-on exercises in bias detection and correction.", "description": "Work through bias case studies, from Simpson’s paradox to selection bias, with guided solutions.", "outcomes": ["Detect bias types", "Choose correction strategies", "Report limitations"], "tags": ["Analyst", "Bias", "Diagnostics"], "format": "Workshop", "language": "English", "rating": 4.5 }, { "id": "counterfactuals", "title": "Counterfactual Reasoning", "category": "Causal Inference", "level": "Advanced", "price": 329, "durationHours": 12, "shortDescription": "Formal counterfactuals to inform strategic choices.", "description": "Learn the language of potential outcomes and use it to evaluate policies and product changes.", "outcomes": ["Define causal estimands", "Interpret potential outcomes", "Assess policy effects"], "tags": ["Data Scientist", "Potential Outcomes", "Policy"], "format": "Self-paced", "language": "English", "rating": 4.6 }, { "id": "monte-carlo", "title": "Monte Carlo for Decisions", "category": "Bayesian", "level": "Intermediate", "price": 259, "durationHours": 10, "shortDescription": "Simulate uncertainty to make robust choices.", "description": "Use simulation to model risk, forecast ranges, and compare strategies under uncertainty.", "outcomes": ["Build simulators", "Interpret distributions", "Communicate risks"], "tags": ["Analyst", "Simulation", "Risk"], "format": "Self-paced", "language": "English", "rating": 4.6 }, { "id": "uplift-ethics", "title": "Ethical Targeting with Causal ML", "category": "Governance", "level": "Advanced", "price": 289, "durationHours": 10, "shortDescription": "Fairness-aware uplift and treatment policies.", "description": "Integrate fairness metrics into treatment assignment and evaluate disparate impact.", "outcomes": ["Assess fairness", "Mitigate bias", "Document governance"], "tags": ["Causal ML", "Ethics", "Policy"], "format": "Cohort", "language": "English", "rating": 4.6 }, { "id": "sql-experiments", "title": "SQL Patterns for Experiments", "category": "Tooling", "level": "Intermediate", "price": 189, "durationHours": 8, "shortDescription": "Implement experiment pipelines with SQL patterns.", "description": "Randomization checks, exposure windows, metric aggregation, and CUPED in SQL.", "outcomes": ["Implement exposure logic", "Aggregate metrics", "Run diagnostics"], "tags": ["Data Scientist", "SQL", "Experiments"], "format": "Self-paced", "language": "English", "rating": 4.5 }, { "id": "storytelling", "title": "Analytical Storytelling", "category": "Frameworks", "level": "Beginner", "price": 149, "durationHours": 7, "shortDescription": "Tell clear decision stories grounded in evidence.", "description": "Craft narratives that align stakeholders and drive action without overstating certainty.", "outcomes": ["Structure narratives", "Use uncertainty well", "Drive alignment"], "tags": ["Leader", "Communication", "Analyst"], "format": "Self-paced", "language": "English", "rating": 4.4 }, { "id": "metrics-health", "title": "Metrics Health Checks", "category": "Metrics", "level": "Intermediate", "price": 189, "durationHours": 8, "shortDescription": "Detect metric drift, instability, and anomalies.", "description": "Build automated checks for stability and interpretability to keep metrics trustworthy over time.", "outcomes": ["Drift detection", "Alerting thresholds", "Diagnostics reporting"], "tags": ["Analyst", "Product Manager", "Metrics"], "format": "Workshop", "language": "English", "rating": 4.5 }, { "id": "sequential", "title": "Sequential Testing Methods", "category": "Experiments", "level": "Advanced", "price": 319, "durationHours": 12, "shortDescription": "Alpha-spending and safe tests for continuous monitoring.", "description": "Understand optional stopping, alpha-spending, and safe test approaches for valid real-time decisions.", "outcomes": ["Use alpha-spending", "Apply safe tests", "Maintain error control"], "tags": ["Data Scientist", "Experiments", "Sequential"], "format": "Cohort", "language": "English", "rating": 4.7 } ]