About
This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python™ programming language.
Course Homepage: 16.00 Introduction to Computer Science and Programming
Course features at MIT OpenCourseWare page: *Exams *Assignments
Videos

Lecture 3: Common code patterns: iterative programs
Apr 17, 2010
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11395 views

Lecture 8: Complexity; log, linear, quadratic, exponential algorithms
Apr 17, 2010
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7876 views

Lecture 1: Goals of the course; what is computation; introduction to data types,...
Apr 17, 2010
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51970 views

Lecture 13: Dynamic programming: overlapping subproblems, optimal substructure
Apr 17, 2010
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6965 views

Lecture 16: Encapsulation, inheritance, shadowing
Apr 17, 2010
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4510 views

Lecture 11: Testing and debugging
Apr 17, 2010
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5974 views

Lecture 10: Divide and conquer methods, merge sort, exceptions
Apr 17, 2010
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6434 views

Lecture 17: Computational models: random walk simulation
Apr 17, 2010
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5825 views

Lecture 7: Lists and mutability, dictionaries, pseudocode, introduction to effic...
Apr 17, 2010
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6815 views

Lecture 14: Analysis of knapsack problem, introduction to object-oriented progra...
Apr 17, 2010
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7212 views

Lecture 2: Operators and operands; statements; branching, conditionals, and iter...
Apr 17, 2010
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18508 views

Lecture 12: More about debugging, knapsack problem, introduction to dynamic prog...
Apr 17, 2010
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6718 views

Lecture 23: Stock market simulation
Apr 17, 2010
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13273 views

Lecture 15: Abstract data types, classes and methods
Apr 17, 2010
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5000 views

Lecture 21: Validating simulation results, curve fitting, linear regression
Apr 17, 2010
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5714 views

Lecture 9: Binary search, bubble and selection sorts
Apr 17, 2010
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5776 views

Lecture 18: Presenting simulation results, Pylab, plotting
Apr 17, 2010
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4266 views

Lecture 22: Normal, uniform, and exponential distributions; misuse of statistics...
Apr 17, 2010
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4645 views

Lecture 20: Monte Carlo simulations, estimating
Apr 17, 2010
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8141 views

Lecture 24: Course overview; what do computer scientists do?
Apr 17, 2010
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4761 views

Lecture 19: Biased random walks, distributions
Apr 17, 2010
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4038 views

Lecture 4: Decomposition and abstraction through functions; introduction to recu...
Apr 17, 2010
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9681 views

Lecture 5: Floating point numbers, successive refinement, finding roots
Apr 17, 2010
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7494 views

Lecture 6: Bisection methods, Newton/Raphson, introduction to lists
Apr 17, 2010
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7426 views