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Home » Applied Sciences » Computer Science » Introduction to Computer Science and Programming (Fall 2008 MIT) » 17 Computational Models Random Walk Simulation

17 Computational Models Random Walk Simulation

Course:Introduction to Computer Science and Programming (Fall 2008 MIT)
Discipline:Applied Sciences
Institute:MIT
Instructor(s): https://youtu.be/ZbIpjf0QEPI?list=PL4C4720A6F225E074
Level:Undergraduate

Introduction to Computer Science and Programming (Fall 2008 MIT)

1 Introduction and Goals; Data Types, Operators, and Variables
10 Divide and Conquer Methods, Merge Sort, Exceptions
11 Testing and Debugging
12 Debugging, Knapsack Problem, Introduction to Dynamic Programming
13 Dynamic Programming Overlapping Subproblems, Optimal Substructure
14 Introduction to Object-oriented Programming
15 Abstract Data Types, Classes and Methods
16 Encapsulation, Inheritance, Shadowing
17 Computational Models Random Walk Simulation
18 Presenting Simulation Results, Pylab, Plotting
19 Biased Random Walks, Distributions
2 Branching, Conditionals, and Iteration
20 Monte Carlo Simulations, Estimating pi
21 Validating Simulation Results, Curve Fitting, Linear Regression
22 Normal, Uniform, and Exponential Distributions
23 Stock Market Simulation
24 Course Overview; What Do Computer Scientists Do?
3 Common Code Patterns Iterative Programs
4 Abstraction through Functions; Introduction to Recursion
5 Floating Point Numbers, Successive Refinement, Finding Roots

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