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Free Learn With Nathan Academy book

AI Foundations

A practical, plain-language foundation for understanding and using artificial intelligence.

The learner is overwhelmed by AI terminology and cannot identify a safe, useful starting point. From confused about AI to able to explain where it fits and choose a practical first use case.

The complete book is free. No fee or credit card required.

Author
Nathan Thiyagarajah
Chapters
15
Reading time
About 7 hours
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Book contents

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  1. 01
    AI for Absolute Beginners: What You Actually Need to KnowA plain-English starting point that turns “AI feels confusing” into one useful, safe action you can take this week.
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  2. 02
    What AI Can Do for a Small Business TodayA practical way to find useful AI work without buying technology first or gambling with customer trust.
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  3. 03
    ChatGPT vs Claude vs Gemini vs Copilot: Which Should You Use?Choose a primary AI assistant by matching the product to your work, data, ecosystem, and review process—not to a leaderboard headline.
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  4. 04
    AI Chatbots vs AI Assistants vs AI AgentsUnderstand the practical difference by following who chooses the next step, which tools are available, and what the system is permitted to change.
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  5. 05
    10 Tasks You Should Stop Doing ManuallyFind ten practical places where AI can remove the repetitive first pass while you keep the context, verification, and final decision.
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  6. 06
    How Large Language Models Work Without the Technical JargonBuild a useful mental model of tokens, training, attention, prediction, and generation—without pretending the system thinks like a person.
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  7. 07
    What Is Generative AI?Understand what makes an AI system generative, how generation differs from search and classification, and where human judgment still belongs.
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  8. 08
    What Is Multimodal AI?Learn how AI can work across text, images, audio, video, and documents—and why combining modes still requires careful verification.
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  9. 09
    Free AI vs Paid AI: When Is It Worth Paying?Replace feature-list shopping with a simple business test based on value, limits, workflow fit, privacy, and total cost.
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  10. 10
    Understanding AI HallucinationsRecognize plausible falsehoods, understand why they occur, and build a verification workflow that matches the consequence of the claim.
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  11. 11
    Why AI Sometimes Gives Bad AnswersDiagnose weak AI output systematically by checking the task, input, context, model, tools, and review process in the right order.
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  12. 12
    Models, Context Windows and Tokens ExplainedUnderstand the three limits behind every AI conversation so you can choose a model, manage long inputs, and reserve space for a useful answer.
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  13. 13
    AI Privacy: What Should You Never Upload?Use a practical data gate to keep credentials, unauthorized personal information, and confidential material out of unapproved AI tools.
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  14. 14
    How to Safely Use AI With Business InformationTurn privacy principles into an operating workflow with data classes, approved tools, least privilege, human approval, and incident-ready records.
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  15. 15
    Where AI Is Heading: From Chatbots to Autonomous SystemsPrepare for more capable and connected AI without betting your business on one forecast: build modular workflows, evidence, evaluation, and control.
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