Probabilistic Forecasting Mastery

Valeriy Manokhin

Probabilistic Forecasting Expert

From fragile point forecasts to decision-grade probabilistic forecasting

Probabilistic forecasting is hot — because point forecasts no longer suffice.

Probabilistic forecasting has shifted from a niche topic to a critical professional skill. In planning, finance, energy, supply chains, and operations, decisions are not made on a single number — they are made under uncertainty, risk, and asymmetric costs.

Yet most teams are unprepared. They can generate point forecasts, but struggle to produce uncertainty that is calibrated, interpretable, and defensible. Intervals are often wrong, metrics misaligned with decisions, and “uncertainty” collapses outside notebooks. When stakeholders ask, “Can we trust this?”, there is no clear answer.

This course closes that gap.

You’ll learn how to build decision-grade probabilistic forecasts: quantiles, predictive distributions, proper scoring rules, calibration diagnostics, and evaluation frameworks aligned with real business outcomes. This is not about hype or exotic models. It’s about mastering methods that work in production and hold up under scrutiny.

Probabilistic forecasting is hot for a simple reason: real decisions are probabilistic — forecasts must be too.

What you’ll learn

Move from point forecasts to decision-grade probabilistic forecasts you can trust, explain, and defend in production.

Learn how to produce uncertainty that is statistically valid, stable over time, and reliable in real deployments.

Translate probabilistic outputs into clear narratives and visuals that decision-makers understand and act on.

Correctly generate quantiles, intervals, and full predictive distributions using modern, proven methods.

Use scoring rules that reward good uncertainty and reflect real business costs, not misleading accuracy metrics.

Identify under- or over-confidence early and apply fixes before miscalibration causes downstream failures.

Gain the technical and conceptual authority to defend forecasts, challenge assumptions, and guide teams.

Learn directly from Valeriy

Valeriy Manokhin

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ML expert and 7× book author building AI forecasting systems

Who this course is for

Senior DS/ML engineers who ship forecasts and need calibrated uncertainty, proper evaluation, and production-ready probabilistic outputs.
Forecasting & planning leads who own business decisions and need uncertainty they can explain, defend, and align with costs and risk.
Executives/tech leaders who rely on forecasts and want mental models to challenge assumptions and steer strategy under uncertainty.