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MIT OpenCourseWare is an initiative to make course materials from all MIT subjects freely available on the web, so that anyone can access and use them.
The course is intended for students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students.
This course introduces students to machine learning in healthcare, including the nature of clinical data, disease progression modeling, precision medicine, diagnosis, subtype discovery, and improving clinical workflows.
This course discusses the evolution and role of urban public transportation modes, systems, and services, focusing on bus and rail.
This course concentrates on close analysis and criticism of a wide range of films, from the early silent period, classic Hollywood genres including musicals, thrillers and westerns, and European and Japanese art cinema.
This course focuses on science and technology innovation system, including case studies on energy, computing, advanced manufacturing, and health sectors, with an emphasis on public policy and the federal government's role in that system.
This course covers the fundamental principles, practices and tools of Lean Six Sigma methods that underlay modern organizational productivity approaches applied in aerospace, automotive, health care, and other sectors.
This course covers the experimental basis of quantum physics. It introduces wave mechanics, Schrödinger's equation in a single dimension, and Schrödinger's equation in three dimensions.
This course is a survey of the scientific study of human nature, including how the mind works, and how the brain supports the mind
This course provides an introduction to the chemistry of biological, inorganic, and organic molecules.
This subject deals primarily with equilibrium properties of macroscopic systems, basic thermodynamics, chemical equilibrium of reactions in gas and solution phase, and rates of chemical reactions.
This course reviews linear algebra with applications to probability and statistics and optimization–and above all a full explanation of deep learning.
The course emphasizes connections between theoretical concepts and practice using programming tasks and some experiments with real-world communication channels.
This course discusses nonlinear dynamics and control of underactuated mechanical systems, with an emphasis on machine learning methods.
This course introduces students to the modeling, quantification, and analysis of uncertainty.
The course focuses on the application of fundamental principles, toward an understanding of microorganisms as geochemical agents responsible for the evolution and renewal of the biosphere and of their role in human health and disease.
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