Programme Content
Module 1Overview of ML & AILandscape Problem framing The modern AI stackModule 2ML FundamentalsSupervised & unsupervised learning Loss, gradients, generalisationModule 3Creating your first ML ModelHands-on Python Real datasetModule 4Journey from ML to Deep LearningWhen and why DL Architectural intuitionModule 5Training Neural NetworksBackprop Optimisers Regularisation Hands-on