AI For Youth: Grade 11

Categories: Youth
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About Course

This course is an introduction to deep learning. Students build a neural network from a single neuron to a working training loop, covering nonlinearity, loss functions, gradient descent, backpropagation, and what to do when a network will not learn. Features: self-paced, about 1 hour per lesson, 8 lessons, 8 quizzes, 1 project, prerequisite: Grade 10.

Course Content

Unit 1: Neurons and Networks
<p>What a single neuron computes, the boundary it can draw, why one is never enough, and the two pieces that turn a pile of neurons into something that can learn: nonlinearity and a loss function. Lessons 1 through 4.</p>

  • Lesson 1: The Neuron and the Perceptron
  • Quiz 1: The Neuron and the Perceptron
  • Lesson 2: The Hidden Layer
  • Quiz 2: The Hidden Layer
  • Lesson 3: Activation Functions and Nonlinearity
  • Quiz 3: Activation Functions and Nonlinearity
  • Lesson 4: The Loss Function
  • Quiz 4: The Loss Function

Unit 2: Training a Network
<p>Gradient descent, backpropagation, and the training loop as it actually runs on a real machine, plus what to do when a network refuses to learn at all. Lessons 5 through 8.</p>

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