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

Neural networks intuition Layers, neurons, and activations Representation learning idea Convolutional networks overview Sequence models overview Attention mechanisms idea Transformers in plain language Foundation models overview Transfer and fine-tuning paths Prompting and chaining basics RAG and grounding concepts Multimodal models overview Scaling laws intuition Strengths and weaknesses Everyday DL use cases

9Workflows for ML and Data Science

10Choosing and Scoping AI Projects

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/Non-Technical Deep Learning

Non-Technical Deep Learning

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Demystify deep learning concepts with plain-language intuition.

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Scaling laws intuition

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