Duration: 75 Minutes

Description

Introduces Machine Learning as the engine behind modern AI solutions and explains how organisations use data to build predictive models.

Topics Covered

  • What is Machine Learning?
  • Types of Machine Learning
    • Supervised Learning
    • Unsupervised Learning
    • Reinforcement Learning
  • Training Data
  • Algorithms
  • Model Accuracy
  • Overfitting
  • Model Drift
  • Business Applications

Learning Outcomes

Participants will:

  • Explain Machine Learning concepts.
  • Differentiate learning approaches.
  • Understand why data quality matters.
  • Identify common Machine Learning risks.
  • Recognise governance responsibilities.

Executive Discussion

Should the Board approve AI models without understanding how they were trained?

SkillSim Exercise

Review three predictive models and decide which one should be approved for production.

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