BeginnerÚtvonal · Szabad

AI alapok

Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.

4Modulok
11Útmutatók
~4hBefejezni

Loading your course evidence…

Eredmények

Mit tudsz majd csinálni

  • Explain training and inference in plain language.
  • Separate demonstrated capability from marketing claims.
  • Evaluate AI outputs using evidence, uncertainty, and fit-for-purpose tests.

Prerequisites:None.

Tanterv

Kurzusmodulok

  1. What AI is

    Eredmény: Distinguish AI, machine learning, and ordinary software.

    Gyakorlás: Classify five everyday systems and explain which definition of AI you used.

    AI concepts and boundaries
  2. How systems learn

    Eredmény: Describe the role of examples, objectives, and generalization.

    Gyakorlás: Diagnose why a model can perform well in testing but fail for a new population.

    Data, training, and generalization
  3. Models and inference

    Eredmény: Explain what happens when a trained model produces an output.

    Gyakorlás: Trace one user request from input through model output and human review.

    Modellek, következtetések és korlátok
  4. Evidence and uncertainty

    Eredmény: Check claims, benchmarks, and confident-sounding outputs.

    Gyakorlás: Create a claim ledger for one AI product announcement.

    Értékelés és mérföldkőfej műveltségUncertainty and confidence calibrationForrás- és igényellenőrzés

Alkalmazott zárókő

AI claim fact check

Choose one public AI claim and produce a one-page evidence review for a nontechnical reader.

  • Original claim and source
  • Two supporting or contradicting sources
  • Known limitations
  • Plain-language conclusion with confidence