AI Fluency -AI Capabilities & Limitations
FoundationThis half-day builds an accurate mental model of what a large language model is actually doing — prediction, patterns and probability — with no mathematics. You learn what the model knows and when it stopped learning, why it forgets, and why the same question returns different answers. You then work the two sides honestly: where AI is genuinely excellent, which is more than most sceptics admit, and where it fails, which is more than most enthusiasts admit. You will deliberately induce a hallucination, watch how convincing it is, and then design a check that catches it. You leave with a practical decision rule for when to trust it.
Program Fee
Offer ends: 8/31/2026
1-on-1 doubt clearing · WhatsApp group · Post-training Q&A
Request Syllabus / Call BackProgram Overview
The most expensive AI mistakes are made by people who trusted a confident answer. This half-day builds an accurate mental model of what a large language model is actually doing — prediction, patterns and probability — with no mathematics. You learn what the model knows and when it stopped learning, why it forgets, and why the same question returns different answers. You then work the two sides honestly: where AI is genuinely excellent, which is more than most sceptics admit, and where it fails, which is more than most enthusiasts admit. You will deliberately induce a hallucination, watch how convincing it is, and then design a check that catches it. You leave with a practical decision rule for when to trust it.
What You'll Learn
- Describe how a large language model works, without mathematics
- Explain the knowledge cutoff, context limits, and why the model forgets
- Explain why the same question can return different answers
- Identify where AI genuinely excels — language, structure, synthesis, transformation
- Recognise hallucination, and understand why confidence is not accuracy
- Identify bias, blind spots and the hard limits — real-time facts, arithmetic, causation
- Apply a practical decision rule for when to trust AI output and when to verify
Who Can Join
- •Executives, managers and analysts
- •Anyone making decisions with AI-assisted information
- •Teams adopting AI without a clear policy
- •Anyone who has been burned by a confident wrong answer
PREREQUISITES
• None
• No coding required
Curriculum
→ A mental model, no mathematics
→ Training and the cutoff
→ Context and memory
→ Why the same question gives different answers
→ Lab 0
Total: 3h across 2 modules
Tools & Technologies
Projects Included
- ▹ Lab 0 — Probe the model’s boundaries: knowledge cutoff, memory and consistency
- ▹ Lab M01 — Deliberately induce a hallucination, then design a check that catches it
Official Certifications
Assessment is continuous and practical: 2 Applied Learning Labs (60%) and an end-of-course practical assessment (40%). Passing mark 80%, plus completion of all 2 labs and full attendance. The CertTulen Course Completion Certificate is awarded on meeting that standard.
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