Online courses directory (2511)
This course will explore the rich diversity of women's voices and experiences as reflected in writings and films by and about Latina writers, filmmakers, and artists. Through close readings, class discussions and independently researched student presentations related to each text, we will explore not only the unique, individual voice of the writer, but also the cultural, social and political contexts which inform their narratives. We will also examine the roles that gender, familial ties and social and political preoccupations play in shaping the values of the writers and the nature of the characters encountered in the texts and films.
An opportunity for graduate study of advanced subjects in Brain and Cognitive Sciences not included in other subject listings. The key topics covered in this course are Bipolar Disorder, Psychosis, Schizophrenia, Genetics of Psychiatric Disorder, DISC1, Ca++ Signaling, Neurogenesis and Depression, Lithium and GSK3 Hypothesis, Behavioral Assays, CREB in Addiction and Depressive Behaviors, The GABA System-I, The GABA System-II, The Glutamate Hypothesis of Schizophrenia, The Dopamine Pathway and DARPP32.
This project-based course will explore the future of textiles, focusing particularly on blending rich crafting traditions with new technologies. Topics will include textile-based electronics, textile fabrication, algorithmic pattern design, and composites. We will experiment with a wide range of fibers, yarns, and fabrics including traditional materials like wool and cotton as well as metal fibers and yarns, fusible plastics, papers, and resins. We will also explore techniques like felting, laser cutting, CNC knitting, digital printing, and CNC embroidery. Students will complete weekly hands-on assignments and a final project.
WARNING NOTICE:
An activity described in this course is potentially hazardous and requires a high level of safety training, special facilities and equipment, and supervision by appropriate individuals. You bear the sole responsibility, liability, and risk for the implementation of such safety procedures and measures. MIT shall have no responsibility, liability, or risk for the content or implementation of any of the material presented. Legal Notice
Humans are social animals; social demands, both cooperative and competitive, structure our development, our brain and our mind. This course covers social development, social behaviour, social cognition and social neuroscience, in both human and non-human social animals. Topics include altruism, empathy, communication, theory of mind, aggression, power, groups, mating, and morality. Methods include evolutionary biology, neuroscience, cognitive science, social psychology and anthropology.
6.541J surveys the structural properties of natural languages, with special emphasis on the sound pattern. Topics covered include: representation of the lexicon; physiology of speech production; articulatory phonetics; acoustical theory of speech production; acoustical and articulatory descriptions of phonetic features and of prosodic aspects of speech; perception of speech; models of lexical access and of speech production and planning; and applications to recognition and generation of speech by machine, and to the study of speech disorders.
This course is for upper-level graduate students who are planning careers in computational neuroscience. This course focuses on the problem of supervised learning from the perspective of modern statistical learning theory starting with the theory of multivariate function approximation from sparse data. It develops basic tools such as Regularization including Support Vector Machines for regression and classification. It derives generalization bounds using both stability and VC theory. It also discusses topics such as boosting and feature selection and examines applications in several areas: Computer Vision, Computer Graphics, Text Classification, and Bioinformatics. The final projects, hands-on applications, and exercises are designed to illustrate the rapidly increasing practical uses of the techniques described throughout the course.
This course discusses the principles and methods of statistical mechanics. Topics covered include classical and quantum statistics, grand ensembles, fluctuations, molecular distribution functions, other concepts in equilibrium statistical mechanics, and topics in thermodynamics and statistical mechanics of irreversible processes.
Statistical Mechanics is a probabilistic approach to equilibrium properties of large numbers of degrees of freedom. In this two-semester course, basic principles are examined. Topics include: Thermodynamics, probability theory, kinetic theory, classical statistical mechanics, interacting systems, quantum statistical mechanics, and identical particles.
This is the second term in a two-semester course on statistical mechanics. Basic principles are examined in this class, such as the laws of thermodynamics and the concepts of temperature, work, heat, and entropy. Topics from modern statistical mechanics are also explored, including the hydrodynamic limit and classical field theories.
This course is divided into two sections, Part I and Part II. Part I, found here, provides an introduction to statistical theory. A brief review of probability will be given mainly as background material, however, it is assumed to be known. Topics include normal distribution, limit theorems, Bayesian concepts, and testing, among others.
Part II prepares students for the remainder of the econometrics sequence and and can be found by visiting 14.381 Fall 2006.
This course emphasizes statistics as a powerful tool for studying complex issues in behavioral and biological sciences, and explores the limitations of statistics as a method of inquiry. The course covers descriptive statistics, probability and random variables, inferential statistics, and basic issues in experimental design. Techniques introduced include confidence intervals, t-tests, F-tests, regression, and analysis of variance. Assignments include a project in data analysis.
This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices.
This course is an elective subject in MIT’s undergraduate Energy Studies Minor. This Institute-wide program complements the deep expertise obtained in any major with a broad understanding of the interlinked realms of science, technology, and social sciences as they relate to energy and associated environmental challenges.
This course covers probability distributions for classical and quantum systems. Topics include: Microcanonical, canonical, and grand canonical partition-functions and associated thermodynamic potentials. Also discussed are conditions of thermodynamic equilibrium for homogenous and heterogenous systems.
The course follows 8.044, Statistical Physics I, and is second in this series of undergraduate Statistical Physics courses.
Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution.
This course provides an introduction to the physical chemistry of biological systems. Topics include: connection of macroscopic thermodynamic properties to microscopic molecular properties using statistical mechanics, chemical potentials, equilibrium states, binding cooperativity, behavior of macromolecules in solution and at interfaces, and solvation. Example problems include protein structure, genomic analysis, single molecule biomechanics, and biomaterials.
This course explores the theory of self-assembly in surfactant-water (micellar) and surfactant-water-oil (micro-emulsion) systems. It also introduces the theory of polymer solutions, as well as scattering techniques, light, x-ray, and neutron scattering applied to studies of the structure and dynamics of complex liquids, and modern theory of the liquid state relevant to structured (supramolecular) liquids.
This course is an introduction to statistical data analysis. Topics are chosen from applied probability, sampling, estimation, hypothesis testing, linear regression, analysis of variance, categorical data analysis, and nonparametric statistics.
This course is a broad treatment of statistics, concentrating on specific statistical techniques used in science and industry. Topics include: hypothesis testing and estimation, confidence intervals, chi-square tests, nonparametric statistics, analysis of variance, regression, correlation, decision theory, and Bayesian statistics.
This course offers an in-depth the theoretical foundations for statistical methods that are useful in many applications. The goal is to understand the role of mathematics in the research and development of efficient statistical methods.
Have you ever considered going to a pharmacy to order some new cardiomyocytes (heart muscle cells) for your ailing heart? It might sound crazy, but recent developments in stem cell science have made this concept not so futuristic. In this course, we will explore the underlying biology behind the idea of using stem cells to treat disease, specifically analyzing the mechanisms that enable a single genome to encode multiple cell states ranging from neurons to fibroblasts to T cells. Overall, we hope to provide a comprehensive overview of this exciting new field of research and its clinical relevance.
This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn about current biological research in a highly interactive setting. Many instructors of the Advanced Undergraduate Seminars are postdoctoral scientists with a strong interest in teaching.
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