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AI Foundations / Module 1 / Module 1 · 57-75 minutes

Module 1 · 57-75 minutes

AI Concepts Without the Hype

Look past product labels and classify systems from observable facts, methods, controls, and evidence gaps.

Module resultLearners classify important AI categories and explain models, data, training, and inference without relying on marketing labels or human-like language.

What you will practise

  • Describe a system through its objective, inputs, mechanism, outputs, and influence.
  • Distinguish fixed rules, machine learning, deep learning, generative AI, retrieval, tool-using assistants, and composite or agentic systems.
  • Separate a model from the complete application around it.
  • Distinguish training, evaluation, deployment, and inference.
  • Mark a classification as uncertain and name the missing evidence.

Module sequence

  1. Welcome to Module 1: Look Past the LabelWhy labels are weak evidence and what you will learn.
  2. What Makes a System AI?Describe goals, inputs, methods, outputs, and effects.
  3. Rules, Machine Learning, Generative AI, and AgentsCompare rules, machine learning, generation, retrieval, tools, and agents.
  4. Models, Data, Training, and UseSeparate training, evaluation, deployment, and inference.
  5. Classify Systems from FactsApply TRACE when evidence is incomplete.
  6. Worked Example: A Policy AssistantMap the parts and controls in a policy assistant.
  7. Applied checkpointClassify eight made-up systems and review model answers.
  8. Knowledge checkCheck your understanding with ten retryable questions.
  9. Module summaryConsolidate the module and prepare for Module 2.

Before you continue

Use only the made-up examples supplied by the course. Do not enter real personal, confidential, client, workplace, health, financial, authentication, or security-sensitive information.

Open the AI-system classification checklist and keep it available for the applied checkpoint.