MIT 课程目录1.docx

1.00 Engineering Computation and Data Science??()??(Subject meets with?1.001)?Prereq:?Calculus I (GIR)?Units: 5-1-6?Lecture:?TR9.30-11,F3-4.30?(1-390)?Recitation:?T12?(1-277) or?T1?(1-277) or?W12?(1-132)??No required or recommended textbooks1.000 Computer Programming for Scientific and Engineering Applications??()??Prereq: None.?Coreq:?18.03?Units: 3-2-7??Presents the fundamentals of computing and computer programming (procedural and object-oriented programming) in an engineering context. Introduces logical operations, floating-point arithmetic, data structures, induction, iteration, and recursion. Computational methods for interpolation, regression, root finding, sorting, searching, and the solution of linear systems of equations and ordinary differential equations. Control of sensors and visualization of scientific data. Draws examples from engineering and scientific applications. Students use the MATLAB programming environment to complete weekly assignments.?R. Juanes1.001 Engineering Computation and Data Science??()?(Subject meets with?1.00)?Prereq:?Calculus I (GIR)?Units: 5-1-6?Lecture:?TR9.30-11,F3-4.30?(1-390)?Recitation:?T12?(1-277) or?T1?(1-277) or?W12?(1-132)??Presents fundamentals of computing and programming in an engineering context with an emphasis on data science. Introduces basics of web computing, data structures, and techniques for data analysis. Includes filtering, linear regression, simple machine learning (clustering and classifiers), and visualization. Surveys techniques for ingesting, processing, analyzing, and visualizing engineering data from a range of fields, including geo-spatial, environment, infrastructure, city dynamics, and numerical experiments. Students use JavaScript and HTML5 programming language to complete weekly assignments. Students taking graduate version complete additional assignments.?J. WilliamsNo required or recommended textbooks1.007 Big Engineering: Small Solutions with a Large Impact??(); first half of term?Prereq: No