AI For Youth: Grade 10

Categories: Youth
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About Course

This course is the second part of the introduction to machine learning. Students build decision trees, logistic regression, and support vector machines by hand, choose features, measure results beyond accuracy, combine weak models into a strong one, and identify the problems these methods cannot solve. Features: self-paced, no calculus or coding, about 45 minutes per lesson, 8 lessons, 8 quizzes, 1 project, prerequisite: Grade 9.

Course Content

Unit 1: Classification Methods
<p>Decision trees, logistic regression and support vector machines, each run by hand on the same ten students — then the work that matters more than the choice between them: the features you hand the model in the first place.</p>

  • Lesson 1: Decision Trees
  • Quiz 1: Decision Trees
  • Lesson 2: Logistic Regression
  • Quiz 2: Logistic Regression
  • Lesson 3: Support Vector Machines
  • Quiz 3: Support Vector Machines
  • Lesson 4: Feature Engineering
  • Quiz 4: Feature Engineering

Unit 2: Evaluating and Improving Models
<p>Why accuracy alone is never enough, how precision and recall pull against each other, how a crowd of weak models beats one clever one, and the exact problem that defeats every method in this course.</p>

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