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  • Courseware 
    BioSci M121: Immunology with Hematology

    BioSci M121: Immunology with Hematology

    Antibodies, antigens, antigen-antibody reactions, cells and tissues of lymphoreticular and hematopoietic systems, and individual and collective components of cell-mediated and humoral immune response,

    Subjects:
    Biology
    Keywords:
    Hematology Immunology
    Resource Type:
    Courseware
     
  • Courseware 
    BioSci 93: DNA to Organisms

    BioSci 93: DNA to Organisms

    Cell biology, biochemistry, genetics, and the biology of organ systems, Covers concepts of building blocks (nucleotides, amino acids, and cells) and of information flow (DNA to proteins, receptors to nuclei, the blood to distant organs, and DNA to offspring)

    Subjects:
    Biology
    Keywords:
    DNA Biochemistry Cytology Biology
    Resource Type:
    Courseware
     
  • Courseware 
    BioSci 94: Organisms to Ecosystems

    BioSci 94: Organisms to Ecosystems

    Patterns of diversity, ecology, and evolutionary biology. Emphasis is on the Tree of Life and how its members are distributed and interact. Partial Course.

    Subjects:
    Biology
    Keywords:
    Biodiversity Ecology Evolution (Biology)
    Resource Type:
    Courseware
     
  • Courseware 
    Visualization for Mathematics, Science, and Technology Education

    Visualization for Mathematics, Science, and Technology Education

    This course is an introduction to principles and techniques of visual communication, and provides opportunities for science and engineering majors to acquire practical skills in the visual computer arts, in a studio environment. Students will learn how to create graphics for print and web, animations, and interactive media, and how to use these techniques to effectively communicate scientific and engineering concepts for learning and teaching. This class involves three hands-on creative projects, which will be presented in class.

    Subjects:
    Computing and Visualisation
    Keywords:
    Information visualization
    Resource Type:
    Courseware
     
  • Courseware 
    Game Theory

    Game Theory

    This course provides a rigorous treatment of non-cooperative solution concepts in game theory, including rationalizability and Nash, sequential, and stable equilibria. It covers topics such as epistemic foundations, higher order beliefs, bargaining, repeated games, reputation, supermodular games, and global games. It also introduces cooperative solution concepts—Nash bargaining solution, core, Shapley value—and develops corresponding non-cooperative foundations.

    Subjects:
    Economics and Mathematics and Statistics
    Keywords:
    Game theory
    Resource Type:
    Courseware
     
  • Courseware 
    Quantum Physics III

    Quantum Physics III

    8.06 is the third course in the three-sequence physics undergraduate Quantum Mechanics curriculum. By the end of this course, you will be able to interpret and analyze a wide range of quantum mechanical systems using both exact analytic techniques and various approximation methods. This course will introduce some of the important model systems studied in contemporary physics, including two-dimensional electron systems, the fine structure of Hydrogen, lasers, and particle scattering.

    Subjects:
    Physics
    Keywords:
    Quantum theory
    Resource Type:
    Courseware
     
  • Courseware 
    Quantum Physics I

    Quantum Physics I

    This is the first course in the undergraduate Quantum Physics sequence. It introduces the basic features of quantum mechanics. It covers the experimental basis of quantum physics, introduces wave mechanics, Schrödinger's equation in a single dimension, and Schrödinger's equation in three dimensions. This presentation of 8.04 by Barton Zwiebach (2016) differs somewhat and complements nicely the presentation of Allan Adams (2013). Adams covers a larger set of ideas; Zwiebach tends to go deeper into a smaller set of ideas, offering a systematic and detailed treatment. Adams begins with the subtleties of superpostion, while Zwiebach discusses the surprises of interaction-free measurements. While both courses overlap over a sizable amount of standard material, Adams discussed applications to condensed matter physics, while Zwiebach focused on scattering and resonances. The different perspectives of the instructors make the problem sets in the two courses rather different.

    Subjects:
    Physics
    Keywords:
    Quantum theory
    Resource Type:
    Courseware
     
  • Courseware 
    Quantum Optical Communication

    Quantum Optical Communication

    6.453 Quantum Optical Communication is one of a collection of MIT classes that deals with aspects of an emerging field known as quantum information science. This course covers Quantum Optics, Single-Mode and Two-Mode Quantum Systems, Multi-Mode Quantum Systems, Nonlinear Optics, and Quantum System Theory.

    Subjects:
    Electronic and Information Engineering and Physics
    Keywords:
    Quantum optics Quantum theory Nonlinear optics
    Resource Type:
    Courseware
     
  • Courseware 
    Wave Propagation

    Wave Propagation

    This course discusses theoretical concepts and analysis of wave problems in science and engineering. Examples are chosen from elasticity, acoustics, geophysics, hydrodynamics, blood flow, nondestructive evaluation, and other applications.

    Subjects:
    Mechanical Engineering and Physics
    Keywords:
    Wave mechanics Wave-motion Theory of
    Resource Type:
    Courseware
     
  • Courseware 
    Statistics for Brain and Cognitive Science

    Statistics for Brain and Cognitive Science

    Provides students with the basic tools for analyzing experimental data, properly interpreting statistical reports in the literature, and reasoning under uncertain situations. Topics organized around three key theories: Probability, statistical, and the linear model. Probability theory covers axioms of probability, discrete and continuous probability models, law of large numbers, and the Central Limit Theorem. Statistical theory covers estimation, likelihood theory, Bayesian methods, bootstrap and other Monte Carlo methods, as well as hypothesis testing, confidence intervals, elementary design of experiments principles and goodness-of-fit. The linear model theory covers the simple regression model and the analysis of variance. Places equal emphasis on theory, data analyses, and simulation studies.

    Subjects:
    Mathematics and Statistics and Biology
    Keywords:
    Statistics Cognitive science
    Resource Type:
    Courseware