EE-Learning
Lists and mutability, dictionaries, pseudocode, introduction to efficiency
Catogry:
Computing
Subject:
Computer Science
Course:
Introduction To Computer Science And Programming
Lecture List
Course overview; what do computer scientists do?
Stock market simulation
Normal, uniform, and exponential distributions; misuse of statistics
Validating simulation results, curve fitting, linear regression
Monte Carlo simulations, estimating pi
Biased random walks, distributions
Presenting simulation results, Pylab, plotting
Computational models: random walk simulation
Encapsulation, inheritance, shadowing
Abstract data types, classes and methods
Analysis of knapsack problem, introduction to object-oriented programming
Dynamic programming: overlapping subproblems, optimal substructure
More about debugging, knapsack problem, introduction to dynamic programming
Testing and debugging
Divide and conquer methods, merge sort, exceptions
Binary search, bubble and selection sorts
Complexity; log, linear, quadratic, exponential algorithms
Lists and mutability, dictionaries, pseudocode, introduction to efficiency
Bisection methods, Newton/Raphson, introduction to lists
Floating point numbers, successive refinement, finding roots
Decomposition and abstraction through functions; introduction to recursion
Common code patterns: iterative programs
Operators and operands; statements; branching, conditionals, and iteration
Introduction