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Neural decoding through Machine Learning has become an ever-important tool for neuroscientists to understand how the brain processes information. This course introduces students to this exciting field with seminar-style lectures and hands-on practice sessions. The course will be organized around a number of corner-stone applications of neural decoding in Cognitive Neuroscience, topics include face recognition, concept knowledge representation, and bridging language model and the brain. In the practice sessions, students will learn to analyze actual neuroimaging data and replicate the published findings with off-the-shelf software. By the end of the course, students will be familiar with the basic methods of neural decoding, and acquire hands-on experience of data analysis. Prior programming knowledge is not required and programming skill per se is not part of the evaluation, yet students are expected to familiarize themselves with the scripting interface and understand the basics through the practice sessions. If an interested student has taken a statistics course comparable to one of the listed prerequisite courses, contact the instructor and include the course number and description.