Biased random walks, distributions
Goals of the course; what is computation; introduction to data types, operators, and variables
Operators and operands; statements; branching, conditionals, and iteration
Decomposition and abstraction through functions; introduction to recursion
Floating point numbers, successive refinement, finding roots
Lists and mutability, dictionaries, pseudocode, introduction to efficiency
More about debugging, knapsack problem, introduction to dynamic programming
Dynamic programming: overlapping subproblems, optimal substructure
Analysis of knapsack problem, introduction to object-oriented programming
Course overview; what do computer scientists do?
Validating simulation results, curve fitting, linear regression
Normal, uniform, and exponential distributions; misuse of statistics