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1 - Goals of the Course, what is Compilation,Introduction to Data Types,Operators, and Variables

2 - Operators and Operands, Statements, Branching, Conditionals and Iteration

3 - Common Code Patterns: Iterative Programs

4 - Decomposition and abstraction through functions: introduction to recursion

5 - Floating Point numbers, succesive refinement,finding roots

6 - Bisectionmethods Newton/Raphson, Introduction to Lists

7 - Lists and Mutability, dictionaries,pseudocode,introduction to efficiency

8 - Complexity;log, linear, quadratic, exponential algorithms

9 - Binary Search, buuble 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- Encapsulaton , inheritance, shadowing

17- Computational models: random walk simulation

18- Presenting simulation results , Pylab, Plotting

19- Biased Random Walks, distributions

20- Monte Carlo simulation, 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?