Skip to content
GyaniX
Create account
← Assessment catalogue

Technology

AI & Machine Learning Fundamentals Assessment

Learning and self-assessment — AI-reviewed

50 questions75 minutesProctoredLevel: Entry, Junior, Mid-levelEnglishSkill assessment

What this assesses

AI & Machine Learning Fundamentals: 50 questions across 10 topics, about 75 minutes. Questions were drafted with AI and each one checked in a separate evidence-based review (code run, answers recomputed, sources opened); they are not independently expert-validated.

AI-generated and AI-reviewed — not independently expert-validated. For learning and self-assessment only. Not a hiring, academic or professional qualification.

Data & analytics

  • Classification metrics5 q
  • Core algorithms4 q
  • Data splits & leakage5 q
  • Features & preprocessing5 q
  • Generative AI & LLM basics6 q
  • Learning types5 q
  • Neural network basics6 q
  • Overfitting & regularisation4 q
  • Regression metrics5 q
  • Responsible AI5 q

Who it is for

  • • College students
  • • Freshers
  • • Working professionals
  • • Career changers
  • • Career re-entry
  • • Employees
  • • Organisation candidates

Levels: Entry, Junior, Mid-level

Structure

  • • 50 questions in 75 minutes, one attempt
  • • Questions drawn from a bank of AI-reviewed questions, each checked with evidence; your paper is fixed when you start
  • • Timer runs on our server; answers save automatically; you can resume after a disconnection
  • • AI tools and outside help are not allowed

Languages and content status

Available to take in: English. You choose the language before you start, and it stays the same for the whole attempt. If your language is not listed, the assessment is not offered in it yet; nothing is switched after you pay.

Questions were drafted with AI and checked one by one with evidence (code run, answers recomputed, sources opened). They have not been validated by an independent expert.

Sample questions

Practice examples of the question style. They are not part of the live assessment.

  1. 1. Sample: a spam filter flags 50 e-mails as spam; 40 of them really are spam. What is its precision?

    • A. 0.40
    • B. 0.50
    • C. 0.80
    • D. 1.25

  2. 2. Sample: a dataset of 1,000 rows is split 80/20 into training and test sets. How many rows are in the test set?

    • A. 20
    • B. 200
    • C. 800
    • D. 1,000

Proctoring requirements

  • ✓A laptop or desktop (not a phone)
  • ✓Camera and microphone, switched on throughout
  • ✓Full-screen browser; stay on the assessment tab
  • ✓A quiet room, alone
  • ✓Consent is asked before you start
  • ✓Warnings are shown to you; persistent breaches can end the attempt