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    Introduction to Computer Science and Programming ( video)

    Posted By: crazylife
    Introduction to Computer Science and Programming ( video)

    Introduction to Computer Science and Programming
    Video Lectures | MPEG4 Video 480x360 25.00fps | AAC 44100Hz stereo 1411Kbps | 24 lectures, (40 :50) minutes/lecture | 2.7 GB

    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.

    Course Features
    1 Goals of the course; what is computation; 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, 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
    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?