Introduce students to the creative design process, based on the scientific method and peer review, by application of fundamental principles and learning to complete projects according to schedule and within budget. Subject relies on active learning through a major team-based design-and-build project focused on the need for a new consumer product identified by each team. Topics to be learned while teams create, design, build, and test their product ideas include formulating strategies, concepts and modules, and estimation, concept selection, machine elements, design for manufacturing, visual thinking, communication, teamwork, and professional responsibilities.

In this course, you will learn the principles of genetics with application to the study of biological function at the level of molecules, cells, and multicellular organisms, including humans. We will cover structure and function of genes, chromosomes, and genomes; biological variation resulting from recombination, mutation, and selection; population genetics; and the use of genetic methods to modify genes and genomes and analyze protein function, gene regulation, and inherited disease.
This course, based on the MIT course 7.03 Genetics taken by enrolled MIT students, was organized as a three-part series on edX by MIT’s Department of Biology (Note: The third part of the course is not available yet). It is self-paced and free as long as you enroll in the Audit Track option, which you can select after creating a free account on edX.

In this course, you will engage in the biology of cells of higher organisms. You will study the structure, function, and biosynthesis of cellular membranes and organelles; cell growth and oncogenic transformation; transport, receptors, and cell signaling; the cytoskeleton, the extracellular matrix, and cell movements; cell division and cell cycle; functions of specialized cell types. This course emphasizes the current molecular knowledge of cell biological processes as well as the genetic, biochemical, and other experimental approaches that resulted in these discoveries.
This course, based on the MIT course 7.06 Cell Biology taken by enrolled MIT students, was organized as a three-part series on edX by MIT’s Department of Biology. It is self-paced and free as long as you enroll in the Audit Track option, which you can select after creating a free account on edX.

This course is an in-depth adventure through the molecular mechanisms that control the maintenance, expression, and evolution of prokaryotic and eukaryotic genomes. Through lectures and readings of relevant literature, students will explore gene regulation, DNA replication, genetic recombination, transcription, and mRNA translation. The quizzes are designed to build students’ experimental design and data analysis skills.
This course, based on the MIT course 7.28/7.58 Molecular Biology taken by enrolled MIT students, was organized as a three-part series on edX by MIT’s Department of Biology. It is self-paced and free as long as you enroll in the Audit Track option, which you can select after creating a free account on edX.

The Inclusive Teaching Module is both a standalone online resource for those looking to explore materials related to inclusive teaching as well as an integral part of a blended workshop available to use at your own institution. If you are looking to facilitate a blended workshop using this material, please download the Facilitation Guide and Appendix files to get started! 
As part of the Open Learning Library (OLL), this course is free to use. You have the option to sign up and enroll if you want to track your progress, or you can view and use all the materials without enrolling. Resources on OLL allow learners to learn at their own pace while receiving immediate feedback through interactive content and exercises.

This training course is an introduction to the use of the AFNI software suites for the analysis of functional MRI (fMRI) data. It is not intended as an introduction to how fMRI works but is aimed at people who are already doing fMRI data analysis, or those who will be in the near future. 
AFNI (Analysis of Functional NeuroImages) is a leading software suite of C, Python, and R programs and shell scripts, primarily developed for the analysis and display of anatomical and fMRI data. It is freely available for research purposes. 
This event was organized by the Center for Brains, Minds, and Machines (CBMM) Trainee Leadership Council.
CBMM is a multi-institutional NSF Science and Technology Center headquartered at MIT that is dedicated to developing a computationally based understanding of human intelligence and establishing an engineering practice based on that understanding. CBMM brings together computer scientists, cognitive scientists, and neuroscientists to create a new field—the science and engineering of intelligence.

Machine vision. Data wrangling. Reinforcement learning. What do these terms even mean? In AI 101, MIT researcher Brandon Leshchinskiy offers an introduction to artificial intelligence that’s designed specifically for those with little to no background in the subject. The workshop starts with a summary of key concepts in AI, followed by an interactive exercise where participants train their own algorithm. Finally, it closes with a summary of key takeaways and Q/A. All are welcome!

This is a discussion-based interactive seminar on the two major issues that affect Sub-Saharan Africa: HIV/AIDS and Poverty. AIDS and Poverty, seemingly different concepts, are more inter-related to each other in Africa than in any other continent. As MIT students, we feel it is important to engage ourselves in a dynamic discussion on the relation between the two - how to fight one and how to solve the other.

Introduction to the linguistic study of language pathology, concentrating on experimental approaches and theoretical explanations. Discussion of Specific Language Impairment, autism, Down syndrome, Williams syndrome, normal aging, Parkinson’s disease, Alzheimer’s disease, hemispherectomy and aphasia. Focuses on the comparison of linguistic abilities among these syndromes, while drawing clear comparisons with first and second language acquisition. Topics include the lexicon, morphology, syntax, semantics and pragmatics. Relates the lost linguistic abilities in these syndromes to properties of the brain.

Accelerated Introductory Portuguese for Spanish Speakers covers the basics of Portuguese grammar and presents selected cultural aspects of the Lusophone world, with special emphasis on Brazil. Designed as an intensive introductory course equivalent to Portuguese I and II, it is a Portuguese course for native speakers of Spanish or speakers of other languages who have a native-like command of Spanish.

This course will begin with brief overview of what important current research topics are in oceanography (physical, geological, and biological) and how acoustics can be used as a tool to address them. Three typical examples are climate, bottom geology, and marine mammal behavior. Will then address the acoustic inverse problem, reviewing inverse methods (linear and nonlinear) and the combination of acoustical methods with other measurements as an integrated system. Last part of course will concentrate on specific case studies, taken from current research journals. This course is taught on campus at MIT and with simultaneous video at Woods Hole Oceanographic Institution.

The Acoustics of Speech and Hearing is an H-Level graduate course that reviews the physical processes involved in the production, propagation and reception of human speech. Particular attention is paid to how the acoustics and mechanics of the speech and auditory system define what sounds we are capable of producing and what sounds we can sense. Areas of discussion include:

the acoustic cues used in determining the direction of a sound source,

the acoustic and mechanical mechanisms involved in speech production and

the acoustic and mechanical mechanism used to transduce and analyze sounds in the ear.

The 16 lectures in this course cover the topics of adaptive antennas and phased arrays. Both theory and experiments are covered in the lectures. Part one (lectures 1 to 7) covers adaptive antennas. Part two (lectures 8 to 16) covers phased arrays. Parts one and two can be studied independently (in either order). The intended audience for this course is primarily practicing engineers and students in electrical engineering. This course is presented by Dr. Alan J. Fenn, senior staff member at MIT Lincoln Laboratory.
Online Publication

Economists can’t agree on whether investors and markets are rational and efficient, as modern financial theory assumes, or irrational and inefficient, as behavioral economists believe. Drawing on psychology, evolutionary biology, neuroscience, artificial intelligence, and other fields, Prof. Lo cuts through the debate in this course with a new framework—the Adaptive Markets Hypothesis—in which rationality and irrationality coexist.
Topics:

Introduction and Financial Orthodoxy
Rejecting the Random Walk and Efficient Markets
Behavioral Biases and Psychology
The Neuroscience of Decision-Making
Evolution and the Origin of Behavior
The Adaptive Markets Hypothesis
Hedge Funds: The Galapagos Islands of Finance
Applications of Adaptive Markets
The Financial Crisis
Ethics and Adaptive Markets
The Finance of the Future and the Future of Finance

As part of the Open Learning Library (OLL), this course is free to use. You have the option to sign up and enroll if you want to track your progress, or you can view and use all the materials without enrolling. Resources on OLL allow learners to learn at their own pace while receiving immediate feedback through interactive content and exercises.

This is a graduate course on the design and analysis of algorithms, covering several advanced topics not studied in typical introductory courses on algorithms. It is especially designed for doctoral students interested in theoretical computer science.

This course is a first-year graduate course in algorithms. Emphasis is placed on fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Techniques to be covered include amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms. Domains include string algorithms, network optimization, parallel algorithms, computational geometry, online algorithms, external memory, cache, and streaming algorithms, and data structures.

Advanced Analytic Methods in Science and Engineering is a comprehensive treatment of the advanced methods of applied mathematics. It was designed to strengthen the mathematical abilities of graduate students and train them to think on their own.

The course includes survey and special topics designed for graduate students in the brain and cognitive sciences. It emphasizes ethological studies of natural behavior patterns and their analysis in laboratory work, with contributions from field biology (mammology, primatology), sociobiology, and comparative psychology. It stresses mammalian behavior but also includes major contributions from studies of other vertebrates and of invertebrates. It covers some applications of animal-behavior knowledge to neuropsychology and behavioral pharmacology.

This course analyzes the functions of a complex variable and the calculus of residues. It also covers subjects such as ordinary differential equations, partial differential equations, Bessel and Legendre functions, and the Sturm-Liouville theory.

Following a brief classroom discussion of relevant principles, each student in this course completes the paper design of several advanced circuits such as multiplexers, sample-and-holds, gain-controlled amplifiers, analog multipliers, digital-to-analog or analog-to-digital converters, and power amplifiers. One of each student’s designs is presented to the class, and one may be built and evaluated. Associated laboratory assignments emphasize the use of modern analog building blocks. This course is worth 12 Engineering Design Points.