Keentune
Adaptive skill practice — find your level, get sharper.

AI Literacy practice

Use AI wisely — how it works, when to trust it
Understand and use AI wisely — for everyone, not just engineers. How large language models actually work (tokens, context windows, training data vs live facts), why they confidently make things up ("hallucinate") and how to catch it, writing clear prompts, verifying outputs, and what today’s AI can and can’t reliably do — plus the judgment for responsible use: protecting private data, spotting bias, checking citations, using AI agents safely, and knowing when NOT to trust the output. Focuses on durable concepts, not model-version trivia. Distinct from AI & LLMs (the developer skill on building with models — RAG, embeddings, tool calling). Educational — not a substitute for professional advice.
• Meets you at your level — never too easy, never too hard.
• Adapts every question to how you’re doing.
• Tracks your level over time. Skill practice, not a test.
New here? Read the AI Literacy guide
A free 16-minute primer — the mental model, the mistakes beginners make, and what to practise first.
Curriculum
192 concepts across 26 chapters, from foundations through advanced practice — each one a concept the adaptive question bank can teach and test.
A. What AI is and is not
7
B. How machine learning learns
8
C. Data: the fuel and the failure mode
8
D. Language models under the hood
9
E. Generative systems beyond text
7
F. Reliability, hallucination and confidence
8
G. Prompting well
8
H. Verifying AI output
8
I. Evaluation and measurement
7
J. Bias and fairness
8
K. Privacy and confidentiality with AI
7
L. Securing AI systems
8
M. AI-enabled threats and misuse
7
N. Trustworthy AI principles
8
O. Governing AI use
8
P. Human oversight and automation bias
7
Q. AI at work
8
R. Copyright, attribution and AI output
7
S. Inventions, disclosure and AI
6
T. Synthetic media and provenance
7
U. AI agents and tool use
7
V. Choosing and adopting AI tools
7
W. Policy, standards and the wider landscape
7
X. Compute, cost and footprint
6
Y. People, trust and public understanding
7
Z. Talking about AI accurately
7
View the full curriculum →
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