The chapter begins with the introduction of basic modules in modern neural networks. Then, we provide details about transformers, which are state-of-the-art neural network architectures and popular backbones for foundation models. Finally, we summarize major components in large language models, including next-token prediction, decoding, alignment, and parameter-efficient finetuning.