Introduction to Computer Science and Programming MIT Course , Fall 2008 , Prof. Eric Grimson
Course Description :
Introduction, Operators and operands; statements; branching, conditionals, and iteration, Decomposition and abstraction through functions;recursion,
LecturesIntroductionOperators and operands; statements; branching, conditionals, and iterationCommon code patterns: iterative programsDecomposition and abstraction through functions; introduction to recursionFloating point numbers, successive refinement, finding rootsBisection methods, Newton/Raphson, introduction to listsLists and mutability, dictionaries, pseudocode, introduction to efficiencyComplexity; log, linear, quadratic, exponential algorithmsBinary search, bubble and selection sortsDivide and conquer methods, merge sort, exceptionsTesting and debuggingMore about debugging, knapsack problem, introduction to dynamic programmingDynamic programming: overlapping subproblems, optimal substructureAnalysis of knapsack problem, introduction to object-oriented programmingAbstract data types, classes and methodsEncapsulation, inheritance, shadowingComputational models: random walk simulationPresenting simulation results, Pylab, plottingBiased random walks, distributionsMonte Carlo simulations, estimating piValidating simulation results, curve fitting, linear regressionNormal, uniform, and exponential distributions; misuse of statisticsStock market simulationCourse overview; what do computer scientists do?
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