Measure ML Impact & Business Value

本课程是多个项目的一部分。

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位教师： Caio Avelino 另外 1 个

包含在 Coursera Plus • 了解更多 中

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您将学到什么

Map model metrics to business metrics, and define baselines, counterfactuals, and a measurement plan.

Design experiments, compute lift and confidence intervals, and plan guardrails.

Quantify ROI and risk, build an impact dashboard, and craft an executive story with clear next steps.

您将获得的技能

Financial Analysis

Performance Metric

Stakeholder Communications

Power Electronics

Return On Investment

Dashboard Creation

A/B Testing

Business Metrics

Sample Size Determination

Key Performance Indicators (KPIs)

Statistical Methods

Storytelling

Performance Measurement

Data Storytelling

Experimentation

Product Management

Business

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您将学习的工具

Dashboard

要了解的详细信息

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1 项作业

了解顶级公司的员工如何掌握热门技能

积累特定领域的专业知识

向行业专家学习新概念

获得对主题或工具的基础理解

通过实践项目培养工作相关技能

获得可共享的职业证书

该课程共有3个模块

Most ML initiatives stall between “great AUC” and “great business results.” This course closes that gap end to end.

You’ll learn to translate model performance into money by building metric trees that link offline metrics to product KPIs and P&L outcomes.

We’ll design defensible measurement plans with the right counterfactuals (A/B, holdouts, geo, diff-in-diff) and guardrails that prevent “wins” that hurt the business elsewhere.

You’ll practice power and sample size, variance reduction (CUPED), and lift analysis with confidence intervals.Then we turn lift into ROI: incremental revenue or savings, operating costs, payback and NPV, plus sensitivity analysis to reflect uncertainty.

We’ll finish with impact dashboards and an executive narrative that enable clear go/no-go and scale-up decisions.

This course is for professionals involved in planning, evaluating, or implementing ML solutions — including Data Scientists, ML Engineers, Business Analysts, Product Managers, and Technology Leaders.

It’s also suitable for anyone looking to better connect ML outcomes with business value.

Learners should have a basic understanding of Machine Learning concepts and general business workflows, along with an interest in applying data-driven solutions. No advanced coding or mathematics is required.

By the end of this course, you’ll consistently connect model metrics to financial outcomes and communicate impact in a way leaders trust—so teams ship fewer models and deliver more value.

From Model Metrics to Money

In this module, you will connect model metrics to product and business outcomes, define metric trees, North Star and guardrails, baselines, and counterfactuals, and draft a measurement plan with required instrumentation.

涵盖的内容

4个视频 3篇阅读材料

Welcome to Measuring ML Impact • 4分钟

Metric Trees: Translating AUC into Dollars • 8分钟

Baselines, Counterfactuals, and Measurement Plans • 8分钟

Guardrails That Save You From “Winning” the Wrong Way • 10分钟

Welcome to the Course: Course Overview • 5分钟

Beyond Basic A/B Testing • 5分钟

Ungraded Lab: Draft a Measurement Plan for a Churn-Save Model • 30分钟

Proving Impact with Experiments & Quasi-Experiments

This module guides you to choose the right design (A/B, stepped-wedge, geo lift, diff-in-diff, synthetic control), compute power and sample size, and analyze lift with uncertainty.

涵盖的内容

3个视频 2篇阅读材料

Choosing the Design: A/B vs. Geo vs. Diff-in-Diff • 12分钟

Power, Sample Size, and CUPED • 10分钟

Analyzing Lift with Confidence • 11分钟

Double Machine Learning at Scale to Predict Causal Impact of Customer Actions • 5分钟

Ungraded Lab: Design the Experiment for a Personalization Launch • 30分钟

From Lift to ROI: Dollars, Risk, and Executive Storytelling

In this module, you will convert experimental lift to financial impact, account for costs and uncertainty, monitor post-launch, and craft the exec-ready narrative.

涵盖的内容

4个视频 3篇阅读材料 1个作业

ROI, Payback, and NPV for ML • 11分钟

Impact Dashboards and Post-Launch Monitoring • 12分钟

Risk, Ethics, and Guardrails in the Real World • 12分钟

Course Wrap-Up • 3分钟

Reinforcement Learning for Machine Learning Model Deployment: Evaluating Multi-Armed Bandits in MLOps Environments • 5分钟

Ungraded Lab: Build a One-Page ROI Model and Impact Dashboard • 30分钟

Ungraded Project: Prove and Communicate ML Business Value • 60分钟

Measure ML Impact & Business Value • 25分钟

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