BeginnerÚtvonal · Szabad
AI alapok
Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
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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
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 boundariesHow 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 generalizationModels 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 korlátokEvidence 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