Machine Learning (ML) · Advanced level

Advanced level · Module 6 of 6 · 30 guided hours

Machine Learning Capstone

Design, build, deploy, monitor and document the Market Price Early-Warning Service as a professional ML project.

Learning objectives

  • Plan an ML product from user needs to success criteria
  • Build and deploy a reliable, explainable forecasting service
  • Monitor, document and present the system

Topics

  • user needs and decision framing
  • data and backtesting
  • modelling and interpretation
  • deployment
  • monitoring and governance
  • documentation and presentation

Lessons

  1. Lesson 1 Framing the Early-Warning Service

    Define who uses the forecasts, for which decisions, and how success will be measured.

    user needsdecision framingsuccess criteriarisk register

  2. Lesson 2 Data, Baselines and Backtesting

    Prepare the price data, build baselines and set up a backtesting framework.

    data preparationbaselinesbacktesting frameworkper-market reporting

  3. Lesson 3 Modelling and Interpretation

    Develop forecasting models that beat the baselines and explain their behaviour.

    feature-based modelstuning with backtestsinterpretationuncertainty intervals

  4. Lesson 4 Deployment and Monitoring

    Deploy the service, track it and demonstrate drift detection and a retraining response.

    API and batch deploymentexperiment trackingdrift simulationrunbook

  5. Lesson 5 Model Card and Presentation

    Document the system with a model card and present it to decision-makers and technical reviewers.

    model cardintended uselimitationspresentation

Practical activity

Deliver the capstone through five reviewed milestones: framing, data and baselines, modelling, deployment and monitoring, documentation and presentation.

Expected outcomes

  • A portfolio-quality ML system
  • Experience of the full ML life cycle

Assessment

The level project assessed against its criteria with a live demonstration and questions on design choices.

Taught live by an instructor — online or in person. Free course lessons are for self-study and do not lead to a certificate — see registration options.