Course Catalog
Each course page is written for beginners and explains core ideas before the technical details.
Artificial Neural Networks (ANNs)
Intro, structure, training intuition, practical tips, and an interactive playground.
Open ANN course →Backpropagation
Step-by-step explanation of how networks learn from mistakes using gradient ideas.
Open Backpropagation →Convolutional Neural Networks (CNNs)
How machines understand images: filters, feature maps, pooling, and simple projects.
Open CNN course →Recurrent Neural Networks (RNNs)
Modeling sequences: memory, LSTM/GRU basics, and practical guidance for text and time series.
Open RNN course →Applications
Where neural networks are used, ethical considerations, deployment basics.
Open Applications →