AI For Everyone

Chapters

1Orientation and Course Overview

2AI Fundamentals for Everyone

3Machine Learning Essentials

4Understanding Data

5AI Terminology and Mental Models

6What Makes an AI-Driven Organization

7Capabilities and Limits of Machine Learning

8Non-Technical Deep Learning

9Workflows for ML and Data Science

10Choosing and Scoping AI Projects

Aligning to business goals Opportunity discovery methods Feasibility assessments Data availability audits Risk and constraint analysis Estimating impact and ROI Quick wins vs moonshots Pilot scope and resources Defining success metrics Stakeholder and user mapping Compliance and ethics review Build vs buy tradeoffs Vendor pilot evaluation Prioritization frameworks Roadmap and next steps

11Working with AI Teams and Tools

12Case Studies: Smart Speaker and Self-Driving Car

13AI Transformation Playbook

14Pitfalls, Risks, and Responsible AI

15AI and Society, Careers, and Next Steps

Courses/AI For Everyone/Choosing and Scoping AI Projects

Choosing and Scoping AI Projects

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Select high-impact, feasible AI projects and define success clearly.

Content

10 of 15

Stakeholder and user mapping

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