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This course introduces students to the principles of computation. Upon completion of 6.001, students should be able to explain and apply the basic methods from programming languages to analyze computational systems, and to generate computational solutions to abstract problems. Substantial weekly programming assignments are an integral part of the course. This course is worth 4 Engineering Design Points.
MIT OpenCourseWare is a web-based publication of virtually all MIT course content. OCW is open and available to the world and is a permanent MIT activity.
"The lecture notes reference the 15.075 course textbook: Statistics and Data Analysis from Elementary to Intermediate by Ajit C. Tamhane and Dorothy D. Dunlop, Prentice Hall, 2000. They also occasionally refer to: Casella, George, and Roger L. Berger. Statistical Inference. Belmont, CA: Duxbury Press, 1990."
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.