Machine Learning

Create a machine learning prototype in 12 sessions

Primary, secondary of FE

12 sessions

In-class or extracurricular

Basic to advanced programming

Course Summary

  • Student teams design and build a prototype that solves a problem they care about using machine learning altorithms
  • Teams work their way through a range of activities, split across 12 sessions
  • See below for the Scheme of Work, student workbook, and Learning Objectives

Course sessions

Login or sign up now to access all of the sessions

  1. Session 1: Course Launch
  2. Session 2: Natural Language Processing

  3. Session 3: Recommendation Systems

  4. Session 4: Decisions and Ethics

  5. Session 5: Algorithms

  6. Session 6: Python and Orange

  7. Session 7: Screening Ideas

  8. Session 8: Plan your model

  9. Session 9: Request an Expert

  10. Session 10: Build and test your MVP

  11. Session 11: Pitch your MVP

  12. Session 12: Go Further

Core resource

Course workbook for students

  • This printable student A4 workbook contains practical activities
  • Guides you and your students through the course
  • Fully editable, making it easy for you to adapt to meet your needs

Core resource

Scheme of work

  • Get a quick overview of the course structure
  • Review the learning objectives and outcomes for each session