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  1. This course uses the theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Specific topics include: energy models from classical potentials to first-principles approaches; density functional theory and the total-energy pseudopotential method; errors and accuracy of quantitative predictions: thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations...more

  2. This course is intended as an introduction to political philosophy as seen through an examination of some of the major texts and thinkers of the Western political tradition. Three broad themes that are central to understanding political life are focused upon: the polis experience (Plato, Aristotle), the sovereign state (Machiavelli, Hobbes), constitutional government (Locke), and democracy (Rousseau, Tocqueville). The way in which differen...more

  3. This course offers a broad survey of modern European history, from the end of the Thirty Years' War to the aftermath of World War II. Along with the consideration of major events and figures such as the French Revolution and Napoleon, attention will be paid to the experience of ordinary people in times of upheaval and transition. The period will thus be viewed neither in terms of historical inevitability nor as a procession of great men, b...more

  4. This course offers a holistic view of the aircraft as a system, covering: basic systems engineering; cost and weight estimation; basic aircraft performance; safety and reliability; lifecycle topics; aircraft subsystems; risk analysis and management; and system realization. Small student teams retrospectively analyze an existing aircraft covering: key design drivers and decisions; aircraft attributes and subsystems; and operational experien...more

  5. Concentrates on recognizing and solving convex optimization problems that arise in engineering. Topics include: Convex sets, functions, and optimization problems. Basics of convex analysis. Least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems. Optimality conditions, duality theory, theorems of alternative, and applications. Interiorpoint methods. Applications to signal proc...more

  6. The purpose of this course is to introduce you to basics of modeling, design, planning, and control of robot systems. In essence, the material treated in this course is a brief survey of relevant results from geometry, kinematics, statics, dynamics, and control. The course is presented in a standard format of lectures, readings and problem sets. Lectures will be based mainly, but not exclusively, on material in the Lecture Notes. Lectur...more

  7. This course consists of an international analysis of the impact of epidemic diseases on western society and culture from the bubonic plague to HIV/AIDS and the recent experience of SARS and swine flu. Leading themes include: infectious disease and its impact on society; the development of public health measures; the role of medical ethics; the genre of plague literature; the social reactions of mass hysteria and violence; the rise of the g...more

  8. Psychology 116: Neuroscience Lab is a laboratory experience exploring various topics in behavioral neuroscience. Dr. William Grisham is a Professor from UCLAs Department of Physiological Science. Since July of 1996, Dr. Grisham coordinated and taught upper division laboratories in Interdepartmental Program in Neuroscience and Biopsychology majors for UCLA. Furthermore, he participated in selection and development of laboratory exercises...more

  9. This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.

  10. Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.

  11. Topics include: Advanced memory management features of C and C++; the differences between imperative and object-oriented paradigms; the functional paradigm (using LISP) and concurrent programming (using C and C++); brief survey of other modern languages such as Python, Objective C, and C#. Prerequisites: Programming and problem solving at the Programming Abstractions level. Prospective students should know a reasonable amount of C++. Yo...more