###### Computer Science and Engineering  Introduction to Computer Science and Programming
 List Lectures   [ 1 ]  2  3
 # Lecture Name 1 Introduction 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, successive refinement, finding roots 6 Bisection methods, Newton/Raphson, introduction to lists 7 Lists and mutability, dictionaries, pseudocode, introduction to efficiency 8 Complexity; log, linear, quadratic, exponential algorithms 9 Binary search, bubble and selection sorts 10 Divide and conquer methods, merge sort, exceptions

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