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Over the last decade, there has been amazing progress in deep learning AI systems for vision and language, and more and more cognitive neuroscientists are using these tools to study the human brain. This course will give an overview of popular deep learning methods, including convolutional neural networks, recurrent neural networks, variational autoencoders, and transformers, with the goal of addressing two key questions: 1) to what extent do these deep learning systems act like humans, and 2) what questions can they help us answer about the human mind and brain. The class will involve a mix of lectures, hands-on coding assignments, and reading/discussion of primary research articles. The course will focus heavily on vision but will include some topics in language (including large language models) and social cognition.