Introduction to Computer Science and Programming by MIT 2009 - ISBN:0000000000

Introduction to Computer Science and Programming by MIT 2009

Date: 24 May 2011, 07:48

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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.
01- Goals of the course; what is computation; introduction to data types, operators, and variables
02- Operators and operands; statements; branching, conditionals, and iteration
03- Common code patterns: iterative programs
04- Decomposition and abstraction through functions; introduction to recursion
05- Floating point numbers, successive refinement, finding roots
06- Bisection methods, Newton/Raphson, introduction to lists
07- Lists and mutability, dictionaries, pseudocode, introduction to efficiency
08- Complexity; log, linear, quadratic, exponential algorithms
09- Binary search, bubble and selection sorts
10- Divide and conquer methods, merge sort, exceptions
11- Testing and debugging
12- More about debugging, knapsack problem, introduction to dynamic programming
13- Dynamic programming: overlapping subproblems, optimal substructure
14- Analysis of knapsack problem, 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
20- Monte Carlo simulations, estimating pi
21- Validating simulation results, curve fitting, linear regression
22- Normal, uniform, and exponential distributions; misuse of statistics
23- Stock market simulation
24- Course overview; what do computer scientists do?

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