9 modules · 110 lessons · 86 hours

All tracks

Advanced · every module free · 9 challenges

Neural Networks & Deep Learning
10h · 12 lessons

The forward and backward pass built from nothing, then stacked until it is deep.

Making Deep Networks Train
9h · 12 lessons

Splits, the bias-variance recipe, regularization, initialization and the gradient check that finds the bug.

Optimization Algorithms & Tuning
9h · 12 lessons

Mini-batches, momentum, Adam, schedules, and the hyperparameter search that finds the run.

Structuring Machine Learning Projects
9h · 12 lessons

One number to optimize, a human yardstick to beat, and an error analysis that says what to do next.

Convolutional Networks
11h · 14 lessons

The convolution, the layer built from it, and the architectures that made depth work.

Detection, Segmentation & Face Recognition
9h · 12 lessons

Finding where the object is, drawing its outline, and telling one face from another.

Recurrent Networks & Sequence Models
9h · 11 lessons

Recurrence, backpropagation through time, and the gates that fixed its memory.

Word Embeddings
9h · 12 lessons

Turning words into vectors whose geometry means something -- and the tokenizer underneath.

Attention & the Transformer
11h · 13 lessons

The bottleneck, the attention that removed it, and the architecture that dropped recurrence entirely.

The other tracks

Track 01
Foundations
Level
Beginner
Size
6 modules · 47h
Level
Intermediate
Size
9 modules · 70h