Online courses directory (2511)

6.811: Principles and Practice of Assistive Technology (PPAT) is an interdisciplinary, project-based course, centered around a design project in which small teams of students work closely with a person with a disability in the Cambridge area to design a device, piece of equipment, app, or other solution that helps them live more independently.

This course serves as a description and critical assessment of the major issues and stages of developing a pharmaceutical or biopharmaceutical. Topics covered include drug discovery, preclinical development, clinical investigation, manufacturing and regulatory issues considered for small and large molecules, and economic and financial considerations of the drug development process. A multidisciplinary perspective is provided by the faculty, who represent clinical, life, and management sciences. Various industry guests also participate.

This course serves as a description and critical assessment of the major issues and stages of developing a pharmaceutical or biopharmaceutical. Topics covered include drug discovery, preclinical development, clinical investigation, manufacturing and regulatory issues considered for small and large molecules, and economic and financial considerations of the drug development process. A multidisciplinary perspective is provided by the faculty, who represent clinical, life, and management sciences. Various industry guests also participate.

This course serves as a description and critical assessment of the major issues and stages of developing a pharmaceutical or biopharmaceutical. Topics covered include drug discovery, preclinical development, clinical investigation, manufacturing and regulatory issues considered for small and large molecules, and economic and financial considerations of the drug development process. A multidisciplinary perspective is provided by the faculty, who represent clinical, life, and management sciences. Various industry guests also participate.

This course helps in developing skills as science communicators through projects and analysis of theoretical principles. Case studies explore the emergence of popular science communication over the past two centuries and consider the relationships among authors, audiences and media. Project topics are identified early in the term and students work with MIT Museum staff. Projects may include physical exhibits, practical demonstrations, or scripts for public programs.

The principles and practice of tissue engineering (and regenerative medicine) are taught by faculty of the Harvard-MIT Division of Health Sciences and Technology (HST) and Tsinghua University, Beijing, China. The principles underlying strategies for employing selected cells, biomaterial scaffolds, soluble regulators or their genes, and mechanical loading and culture conditions, for the regeneration of tissues and organs in vitro and in vivo are addressed. Differentiated cell types and stem cells are compared and contrasted for this application, as are natural and synthetic scaffolds. Methodology for the preparation of cells and scaffolds in practice is described. The rationale for employing selected growth factors is covered and the techniques for incorporating their genes into the scaffolds are examined. Discussion also addresses the influence of environmental factors including mechanical loading and culture conditions (e.g., static versus dynamic). Methods for fabricating tissue-engineered products and devices for implantation are taught. Examples of tissue engineering-based procedures currently employed clinically are analyzed as case studies.

Archived webcast lecture videos for the Fall 2008 version of this class can be found at the HST.535 Fall 2008 website.

Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world.

This course was recently revised to meet the MIT Undergraduate Communication Requirement (CR). It covers the same content as 18.310, but assignments are structured with an additional focus on writing.

18.311 Principles of Continuum Applied Mathematics covers fundamental concepts in continuous applied mathematics, including applications from traffic flow, fluids, elasticity, granular flows, etc. The class also covers continuum limit; conservation laws, quasi-equilibrium; kinematic waves; characteristics, simple waves, shocks; diffusion (linear and nonlinear); numerical solution of wave equations; finite differences, consistency, stability; discrete and fast Fourier transforms; spectral methods; transforms and series (Fourier, Laplace). Additional topics may include sonic booms, Mach cone, caustics, lattices, dispersion, and group velocity.

This course introduces the design of feedback control systems as applied to a variety of air and spacecraft systems. Topics include the properties and advantages of feedback systems, time-domain and frequency-domain performance measures, stability and degree of stability, the Root locus method, Nyquist criterion, frequency-domain design, and state space methods.

This course surveys a variety of reasoning, optimization and decision making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their application, taken from the disciplines of artificial intelligence and operations research.

Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, and machine learning. Optimization paradigms include linear programming, integer programming, and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes.

This course surveys a variety of reasoning, optimization and decision making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their application, taken from the disciplines of artificial intelligence and operations research.

Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, and machine learning. Optimization paradigms include linear programming, integer programming, and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes.

5.112 is an introductory chemistry course for students with an unusually strong background in chemistry. Knowledge of calculus equivalent to MIT course 18.01 is recommended. Emphasis is on basic principles of atomic and molecular electronic structure, thermodynamics, acid-base and redox equilibria, chemical kinetics, and catalysis. The course also covers applications of basic principles to problems in metal coordination chemistry, organic chemistry, and biological chemistry.

This course provides an introduction to the chemistry of biological, inorganic, and organic molecules. The emphasis is on basic principles of atomic and molecular electronic structure, thermodynamics, acid-base and redox equilibria, chemical kinetics, and catalysis.

In an effort to illuminate connections between chemistry and biology, a list of the biology-, medicine-, and MIT research-related examples used in 5.111 is provided in Biology-Related Examples.

Acknowledgements

Development and implementation of the biology-related materials in this course were funded through an HHMI Professors grant to Prof. Catherine L. Drennan.

This course provides an introduction to the chemistry of biological, inorganic, and organic molecules. The emphasis is on basic principles of atomic and molecular electronic structure, thermodynamics, acid-base and redox equilibria, chemical kinetics, and catalysis. One year of high school chemistry is the expected background for this freshman-level course.

The aims include developing a unified and intuitive view of how electronic structure controls the three-dimensional shape of molecules, the physical and chemical properties of molecules in gases, liquids and solids, and ultimately the assembly of macromolecules as in polymers and DNA. Relationships between chemistry and other fundamental sciences such as biology and physics are emphasized, as are the relationships between the science of chemistry to its applications in environmental science, atmospheric chemistry and electronic devices. 

Acknowledgements

Professor Drennan would like to acknowledge the contributions of MIT Lecturer Dr. Elizabeth Vogel Taylor, Professor Sylvia Ceyer, and Professor Robert Silbey to the development of this course and its materials.

6.826 provides an introduction to the basic principles of computer systems, with emphasis on the use of rigorous techniques as an aid to understanding and building modern computing systems. Particular attention is paid to concurrent and distributed systems. Topics covered include: specification and verification, concurrent algorithms, synchronization, naming, networking, replication techniques (including distributed cache management), and principles and algorithms for achieving reliability.

This course deals with advanced design theories and textual analysis. Emphasis is placed on script analysis in general, as well as the investigation of design principles from a designer's perspective. Students also refine technical skills in rendering and presentation, historical research, and analysis. Class sessions include interaction with student/faculty directors and other staff designers. The goal of this course is for students to approach text with a fresh vision and translate that vision into design for performance.

The course serves as an introduction to the theory and practice behind many of today's communications systems. 6.450 forms the first of a two-course sequence on digital communication. The second class, 6.451 Principles of Digital Communication II, is offered in the spring.

Topics covered include: digital communications at the block diagram level, data compression, Lempel-Ziv algorithm, scalar and vector quantization, sampling and aliasing, the Nyquist criterion, PAM and QAM modulation, signal constellations, finite-energy waveform spaces, detection, and modeling and system design for wireless communication.

This course is the second of a two-term sequence with 6.450. The focus is on coding techniques for approaching the Shannon limit of additive white Gaussian noise (AWGN) channels, their performance analysis, and design principles. After a review of 6.450 and the Shannon limit for AWGN channels, the course begins by discussing small signal constellations, performance analysis and coding gain, and hard-decision and soft-decision decoding. It continues with binary linear block codes, Reed-Muller codes, finite fields, Reed-Solomon and BCH codes, binary linear convolutional codes, and the Viterbi algorithm.

More advanced topics include trellis representations of binary linear block codes and trellis-based decoding; codes on graphs; the sum-product and min-sum algorithms; the BCJR algorithm; turbo codes, LDPC codes and RA codes; and performance of LDPC codes with iterative decoding. Finally, the course addresses coding for the bandwidth-limited regime, including lattice codes, trellis-coded modulation, multilevel coding and shaping. If time permits, it covers equalization of linear Gaussian channels.

This course is an introduction to discrete applied mathematics. Topics include probability, counting, linear programming, number-theoretic algorithms, sorting, data compression, and error-correcting codes. This is a Communication Intensive in the Major (CI-M) course, and thus includes a writing component.

This class introduces students to the interdisciplinary nature of 21st-century engineering projects with three threads of learning: a technical toolkit, a social science toolkit, and a methodology for problem-based learning. Students encounter the social, political, economic, and technological challenges of engineering practice by participating in real engineering projects with faculty and industry; this semester's major project focuses on the engineering and economics of solar cells. Student teams will create prototypes and mixed media reports with exercises in project planning, analysis, design, optimization, demonstration, reporting and team building.