Online courses directory (19947)

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 explores audio synthesis, musical structure, human computer interaction (HCI), and visual presentation for the creation of interactive musical experiences. Topics include audio synthesis; mixing and looping; MIDI sequencing; generative composition; motion sensors; music games; and graphics for UI, visualization, and aesthetics. Weekly programming assignments in python are included. Student teams build an original, dynamic, and engaging interactive music system for their final project.

The aim of this course is to acquaint students with traditional topics in labor economics and to encourage the development of independent research interests. We will cover a systematic development of the theory of labor supply, labor demand, and human capital. Topics include wage and employment determination, turnover, search, immigration, unemployment, equalizing differences, and institutions in the labor market. There will be particular emphasis on the interaction between theoretical and empirical modeling.

This is a course for those who are interested in the challenge posed by massive and persistent world poverty, and are hopeful that economists might have something useful to say about this challenge. The questions we will take up include: Is extreme poverty a thing of the past? What is economic life like when living under a dollar per day? Why do some countries grow fast and others fall further behind? Does growth help the poor? Are famines unavoidable? How can we end child labor—or should we? How do we make schools work for poor citizens? How do we deal with the disease burden? Is micro finance invaluable or overrated? Without property rights, is life destined to be "nasty, brutish and short"? Has globalization been good to the poor? Should we leave economic development to the market? Should we leave economic development to non-governmental organizations (NGOs)? Does foreign aid help or hinder? Where is the best place to intervene?

Topics include productivity effects of health, private and social returns to education, education quality, education policy and market equilibrium, gender discrimination, public finance, decision making within families, firms and contracts, technology, labor and migration, land, and the markets for credit and savings.

The phenomenology and experimental foundations of particle and nuclear physics are explored in this course. Emphasis is on the fundamental forces and particles, as well as composites.

Effective field theory is a fundamental framework to describe physical systems with quantum field theory. Part I of this course covers common tools used in effective theories. Part II is an in depth study of the Soft-Collinear Effective Theory (SCET), an effective theory for hard interactions in collider physics.

This string theory course focuses on holographic duality (also known as gauge / gravity duality or AdS / CFT) as a novel method of approaching and connecting a range of diverse subjects, including quantum gravity / black holes, QCD at extreme conditions, exotic condensed matter systems, and quantum information.

This course aims to develop negotiation skills by active participation in a variety of negotiation settings, and a series of integrative bargaining cases between two and more than two parties over multiple issues. Ethical dilemmas in negotiation are discussed at various times throughout the course.

This course provides an integrated introduction to electrical engineering and computer science, taught using substantial laboratory experiments with mobile robots. Our primary goal is for you to learn to appreciate and use the fundamental design principles of modularity and abstraction in a variety of contexts from electrical engineering and computer science.

Our second goal is to show you that making mathematical models of real systems can help in the design and analysis of those systems. Finally, we have the more typical goals of teaching exciting and important basic material from electrical engineering and computer science, including modern software engineering, linear systems analysis, electronic circuits, and decision-making.

Course Format

This course has been designed for independent study. It includes all of the materials you will need to understand the concepts covered in this subject. The materials in this course include:

• Lecture videos from Spring 2011, taught by Prof. Dennis Freeman
• Recitation videos, developed for OCW Scholar by teaching assistant Kendra Pugh
• Course notes
• Software and design labs
• Homework assignments and additional exercises
• Nano-quizzes and exams with solutions

Content Development

6.003 covers the fundamentals of signal and system analysis, focusing on representations of discrete-time and continuous-time signals (singularity functions, complex exponentials and geometrics, Fourier representations, Laplace and Z transforms, sampling) and representations of linear, time-invariant systems (difference and differential equations, block diagrams, system functions, poles and zeros, convolution, impulse and step responses, frequency responses). Applications are drawn broadly from engineering and physics, including feedback and control, communications, and signal processing.

The objective of this course is to learn the financial tools needed to make good business decisions. The course presents the basic insights of corporate finance theory, but emphasizes the application of theory to real business decisions. Each session involves class discussion, some centered on lectures and others around business cases.

The focus of this course is on financial theory and empirical evidence for making investment decisions. Topics include: portfolio theory; equilibrium models of security prices (including the capital asset pricing model and the arbitrage pricing theory); the empirical behavior of security prices; market efficiency; performance evaluation; and behavioral finance.

This course covers the key quantitative methods of finance: financial econometrics and statistical inference for financial applications; dynamic optimization; Monte Carlo simulation; stochastic (Itô) calculus. These techniques, along with their computer implementation, are covered in depth. Application areas include portfolio management, risk management, derivatives, and proprietary trading.

6.004 offers an introduction to the engineering of digital systems. Starting with MOS transistors, the course develops a series of building blocks — logic gates, combinational and sequential circuits, finite-state machines, computers and finally complete systems. Both hardware and software mechanisms are explored through a series of design examples.

6.004 is required material for any EECS undergraduate who wants to understand (and ultimately design) digital systems. A good grasp of the material is essential for later courses in digital design, computer architecture and systems. The problem sets and lab exercises are intended to give students "hands-on" experience in designing digital systems; each student completes a gate-level design for a reduced instruction set computer (RISC) processor during the semester.

6.005 Software Construction introduces fundamental principles and techniques of software development, i.e., how to write software that is safe from bugs, easy to understand, and ready for change. The course includes problem sets and a final project. Important topics include specifications and invariants; testing; abstract data types; design patterns for object-oriented programming; concurrent programming and concurrency; and functional programming.

The 6.005 website homepage from Spring 2016, along with all course materials, is available to OpenCourseWare users.

This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.

6.012 is the header course for the department's "Devices, Circuits and Systems" concentration. The topics covered include modeling of microelectronic devices, basic microelectronic circuit analysis and design, physical electronics of semiconductor junction and MOS devices, relation of electrical behavior to internal physical processes, development of circuit models, and understanding the uses and limitations of various models. The course uses incremental and large-signal techniques to analyze and design bipolar and field effect transistor circuits, with examples chosen from digital circuits, single-ended and differential linear amplifiers, and other integrated circuits.

This course explores electromagnetic phenomena in modern applications, including wireless and optical communications, circuits, computer interconnects and peripherals, microwave communications and radar, antennas, sensors, micro-electromechanical systems, and power generation and transmission. Fundamentals include quasistatic and dynamic solutions to Maxwell's equations; waves, radiation, and diffraction; coupling to media and structures; guided waves; resonance; acoustic analogs; and forces, power, and energy.

This class will study the behavior of photovoltaic solar energy systems, focusing on the behavior of "stand-alone" systems. The design of stand-alone photovoltaic systems will be covered. This will include estimation of costs and benefits, taking into account any available government subsidies. Introduction to the hardware elements and their behavior will be included.