This course is an introductory exploration of documentary film theory and production, focusing on documentaries about science, engineering, and related fields. Students engage in digital video production as well as social and media analysis of science documentaries. Readings are drawn from social studies of science as well as from documentary film theory. The courses uses documentary video making as a tool to explore the worlds of science and engineering, as well as a tool for thinking analytically about media itself and the social worlds in which science is embedded. The course includes a hands-on lab component devoted to digital video production, in addition to classroom lectures and in-class film screenings.

This course introduces students to the art and formal ideologies of contemporary dance. We explore the aesthetic and technical underpinnings of contemporary dance composition. Basic compositional techniques are discussed and practiced, with an emphasis on principles such as weight, space, time, effort, and shape. Principles of musicality are considered and developed by each student. Working with each other as the raw material of the dance, students develop short compositions that reveal their understanding of basic techniques. Hopefully, students come to understand a range of compositional possibilities available to artists who work with the medium of the human body.

This subject offers a broad survey of texts (both literary and philosophical) drawn from the Western tradition and selected to trace the immediate intellectual antecedents and some of the implications of the ideas animating Darwin’s revolutionary On the Origin of Species. Darwin’s text, of course, is about the mechanism that drives the evolution of life on this planet, but the fundamental ideas of the text have implications that range well beyond the scope of natural history, and the assumptions behind Darwin’s arguments challenge ideas that go much further back than the set of ideas that Darwin set himself explicitly to question - ideas of decisive importance when we think about ourselves, the nature of the material universe, the planet that we live upon, and our place in its scheme of life. In establishing his theory of natural selection, Darwin set himself, rather self-consciously, to challenge a whole way of thinking about these things. The main focus of attention will be Darwin’s contribution to the so-called “argument from design” - the notion that innumerable aspects of the world (and most particularly the organisms within it) display features directly analogous to objects of human design and, since design implies a designer, that an intelligent, conscious agency must have been responsible for their organization and creation. Previously, it had been argued that such features must have only one of two ultimate sources - chance or conscious agency. Darwin proposed and elaborated a third source, which he called Natural Selection, an unconscious agency capable of outdoing the most complex feats of human intelligence.
The course of study will not only examine the immediate inspiration for this idea in the work of Adam Smith and Thomas Malthus and place Darwin’s Origin and the theory of Natural Selection in the history of ensuing debate, but it will also touch upon related issues.

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.

This course introduces methods for harnessing data to answer questions of cultural, social, economic, and policy interest. We will start with essential notions of probability and statistics. We will proceed to cover techniques in modern data analysis: regression and econometrics, design of experiments, randomized control trials (and A/B testing), machine learning, and data visualization.
We will illustrate these concepts with applications drawn from real-world examples and frontier research. Finally, we will provide instruction on the use of the statistical package R, and opportunities for students to perform self-directed empirical analyses.
MITx Online
This course draws materials from 14.310x Data Analysis for Social Scientists, which is part of the MicroMasters Program in Data, Economics, and Design of Policy offered by MITx Online. The MITx Online course is entirely free to audit, though learners have the option to pay a fee, which is based on the learner’s ability to pay, to take the proctored exam and earn a course certificate. To access that course, create an MITx Online account and enroll in the course 14.310x Data Analysis for Social Scientists.

6.263J / 16.37J focuses on the fundamentals of data communication networks. One goal is to give some insight into the rationale of why networks are structured the way they are today and to understand the issues facing the designers of next-generation data networks. Much of the course focuses on network algorithms and their performance. Students are expected to have a strong mathematical background and an understanding of probability theory. Topics discussed include: layered network architecture, Link Layer protocols, high-speed packet switching, queueing theory, Local Area Networks, and Wide Area Networking issues, including routing and flow control.

The MIT Libraries Data Management Group hosts a set of workshops during IAP and throughout the year to assist MIT faculty and researchers with data set control, maintenance, and sharing. This resource contains a selection of presentations from those workshops. Topics include an introduction to data management, details on data sharing and storage, data management using the DMPTool, file organization, version control, and an overview of the open data requirements of various funding sources.

Data that has relevance for managerial decisions is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations such as the internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, and intelligent machines. Such data is often stored in data warehouses and data marts specifically intended for management decision support. Data mining is a rapidly growing field that is concerned with developing techniques to assist managers to make intelligent use of these repositories. A number of successful applications have been reported in areas such as credit rating, fraud detection, database marketing, customer relationship management, and stock market investments. The field of data mining has evolved from the disciplines of statistics and artificial intelligence.
This course will examine methods that have emerged from both fields and proven to be of value in recognizing patterns and making predictions from an applications perspective. We will survey applications and provide an opportunity for hands-on experimentation with algorithms for data mining using easy-to-use software and cases.

This course is designed to introduce first-year Sloan MBA students to the fundamental techniques of using data. In particular, the course focuses on various ways of modeling, or thinking structurally about decision problems in order to make informed management decisions.

This course explores visualization methodologies to conceive and represent systems and data, e.g., financial, media, economic, political, etc., with a particular focus on climate change data in this version of the course. Topics include basic methods for research, cleaning, and analysis of datasets, and creative methods of data presentation and storytelling. The course considers the emotional, aesthetic, ethical, and practical effects of different presentation methods as well as how to develop metrics for assessing impact. Coursework includes readings, visualization exercises, and a final project.

This course addresses information technology fundamentals, including project management and software processes, data modeling, UML, relational databases and SQL. Topics covered include internet technologies, such as XML, web services, and service-oriented architectures. This course provides an introduction to security and presents the fundamentals of telecommunications and includes a project that involves requirements / design, data model, database implementation, website, security and data network. No prior programming experience required.

This course relies on primary readings from the database community to introduce graduate students to the foundations of database systems, focusing on basics such as the relational algebra and data model, schema normalization, query optimization, and transactions. It is designed for students who have taken 6.033 (or equivalent); no prior database experience is assumed, though students who have taken an undergraduate course in databases are encouraged to attend.

This course relies on primary readings from the database community to introduce graduate/undergraduate students to the foundations of database systems, focusing on basics such as the relational algebra and data model, schema normalization, query optimization, transactions, and other more advanced topics. No prior database experience is assumed, though students who have taken an undergraduate course in databases are encouraged to attend.

This course explores natural and electric lighting that integrates occupant comfort, energy efficiency and daylight availability in an architectural context. Students are asked to evaluate daylighting in real space and simulations, and also high dynamic range photography and physical model building.

This resource is to support teachers and educators to run Day of AI activities in their classrooms through curriculum packages and teacher training, all of which is available at no cost to participants.
Developed by leading faculty and educators from MIT RAISE, the curriculum features up to four hours of hands-on activities that engage kids in creative discovery, discussion, and play as they learn the fundamentals of AI, investigate the societal impact of these technologies, and bring artificial intelligence to life through lessons and activities that are accessible to all, even those with no computer science or technical background.

This course is an introduction to the theory and application of large-scale dynamic programming. Topics include Markov decision processes, dynamic programming algorithms, simulation-based algorithms, theory and algorithms for value function approximation, and policy search methods. The course examines games and applications in areas such as dynamic resource allocation, finance and queueing networks.

Foundations and philosophical applications of Bayesian decision theory, game theory and theory of collective choice. Why should degrees of belief be probabilities? Is it always rational to maximize expected utility? If so, why and what is its utility? What is a solution to a game? What does a game-theoretic solution concept such as Nash equilibrium say about how rational players will, or should, act in a game? How are the values and the actions of groups, institutions and societies related to the values and actions of the individuals that constitute them?

This course introduces the D.I.S. method to structure and define real-world problems. The D.I.S., which stands for “Describe, Inquire, State," is a domain-agnostic method for structuring (or defining) ill-structured problems.

Water supply is a problem of worldwide concern: more than 1 billion people do not have reliable access to clean drinking water. Water is a particular problem for the developing world, but scarcity also impacts industrial societies. Water purification and desalination technology can be used to convert brackish ground water or seawater into drinking water. The challenge is to do so sustainably, with minimum cost and energy consumption, and with appropriately accessible technologies.
This subject will survey the state-of-the-art in water purification by desalination and filtration. Fundamental thermodynamic and transport processes which govern the creation of fresh water from seawater and brackish ground water will be developed. The technologies of existing desalination systems will be discussed, and factors which limit the performance or the affordability of these systems will be highlighted. Energy efficiency will be a focus. Nanofiltration and emerging technologies for desalination will be considered. A student project in desalination will involve designing a well-water purification system for a village in Haiti.

Water supply is a problem of worldwide concern: more than 1 billion people do not have reliable access to clean drinking water. Water is a particular problem for the developing world, but scarcity also impacts industrial societies. Water purification and desalination technology can be used to convert brackish ground water or seawater into drinking water. The challenge is to do so sustainably, with minimum cost and energy consumption, and with appropriately accessible technologies.
This subject will survey the state-of-the-art in water purification by desalination and filtration. Fundamental thermodynamic and transport processes which govern the creation of fresh water from seawater and brackish ground water will be developed. The technologies of existing desalination systems will be discussed, and factors which limit the performance or the affordability of these systems will be highlighted. Energy efficiency will be a focus. Nanofiltration and emerging technologies for desalination will be considered. A student project in desalination will involve designing a well-water purification system for a village in Haiti.