Completed Andrew Ng’s Improving Deep Neural Networks — the second in his Deep Learning specialisation — with 100%. Much of the material was familiar from my ML background, but several sections were genuinely valuable: the detailed treatment of optimisation techniques (exponential moving averages, Momentum, RMSProp, Adam), batch normalisation, and dropout.
On to the Convolutional Neural Networks course next.