1 Introduction and Goals; Data Types, Operators, and Variables
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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2 Branching, Conditionals, and Iteration
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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3 Common Code Patterns Iterative Programs
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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4 Abstraction through Functions; Introduction to Recursion
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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5 Floating Point Numbers, Successive Refinement, Finding Roots
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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6 Bisection Methods, Newton/Raphson, Introduction to Lists
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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7 Lists and Mutability, Dictionaries, Introduction to Efficiency
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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8 Complexity Log, Linear, Quadratic, Exponential Algorithms
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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9 Binary Search, Bubble and Selection Sorts
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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10 Divide and Conquer Methods, Merge Sort, Exceptions
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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11 Testing and Debugging
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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12 Debugging, Knapsack Problem, Introduction to Dynamic Programming
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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13 Dynamic Programming Overlapping Subproblems, Optimal Substructure
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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14 Introduction to Object-oriented Programming
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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15 Abstract Data Types, Classes and Methods
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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16 Encapsulation, Inheritance, Shadowing
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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17 Computational Models Random Walk Simulation
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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18 Presenting Simulation Results, Pylab, Plotting
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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19 Biased Random Walks, Distributions
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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20 Monte Carlo Simulations, Estimating pi
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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21 Validating Simulation Results, Curve Fitting, Linear Regression
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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22 Normal, Uniform, and Exponential Distributions
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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23 Stock Market Simulation
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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24 Course Overview; What Do Computer Scientists Do?
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
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Applied Sciences
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6 Bisection Methods, Newton/Raphson, Introduction to List
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Introduction to Computer Science and Programming (Fall 2008 MIT)
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MIT
|
Applied Sciences
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