Level 4 · Precision & Efficiency

The Optimizer

Master forward and backward propagation in three-layer neural networks using advanced mathematical techniques.

  • Module 07
  • 6 sub-modules
  • ~381 min
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Key learning

The subjects this module walks through, in the order the lessons teach them.

  • From Ratio to Gradient Descent
  • Everything Begins with a Ratio
  • Ratio Graph
  • Enter Calculus
  • The Simplest Curved Function
  • What’s the Slope of a Curve?
  • Derivatives in Real Life
  • Why Do We Need the Chain Rule?
  • The Chain Rule
  • Chain Rule Powers Backpropagation
  • The Loss Function: Measuring Our Mistakes
  • The Error Landscape: Hills & Valleys
  • Gradient Descent: Walk Downhill
  • The Learning Rate (α): Getting the Step Size Right
  • Gradient Descent: Numerical Walk-Through
  • Minimizing the Error: What Actually Happens

Every module runs the same loop: theory → quiz → guided lab → lab quiz. See all eight modules →