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6.00 Introduction to Computer Science and Programming

6.00 Introduction to Computer Science and Programming (Fall 2008, MIT OCW). Instructors: Professor Eric Grimson and Professor John Guttag. 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. (from ocw.mit.edu)

Lecture 02 - Branching, Conditionals, and Iteration

Go to the Course Home or watch other lectures:

Lecture 01 - Introduction and Goals; Data Types, Operators, and Variables

Lecture 02 - Branching, Conditionals, and Iteration

Lecture 03 - Common Code Patterns: Iterative Programs

Lecture 04 - Abstraction through Functions; Introduction to Recursion

Lecture 05 - Floating Point Numbers, Successive Refinement, Finding Roots

Lecture 06 - Bisection Methods, Newton/Raphson, Introduction to Lists

Lecture 07 - Lists and Mutability, Dictionaries, Introduction to Efficiency

Lecture 08 - Complexity: Log, Linear, Quadratic, Exponential Algorithms

Lecture 09 - Binary Search, Bubble and Selection Sorts

Lecture 10 - Divide and Conquer Methods, Merge Sort, Exceptions

Lecture 11 - Testing and Debugging

Lecture 12 - Debugging, Knapsack Problem, Introduction to Dynamic Programming

Lecture 13 - Dynamic Programming: Overlapping Subproblems, Optimal Substructure

Lecture 14 - Introduction to Object-oriented Programming

Lecture 15 - Abstract Data Types, Classes and Methods

Lecture 16 - Encapsulation, Inheritance, Shadowing

Lecture 17 - Computational Models: Random Walk Simulation

Lecture 18 - Presenting Simulation Results, Pylab, Plotting

Lecture 19 - Biased Random Walks, Distributions

Lecture 20 - Monte Carlo Simulations, Estimating pi

Lecture 21 - Validating Simulation Results, Curve Fitting, Linear Regression

Lecture 22 - Normal, Uniform, and Exponential Distributions

Lecture 23 - Stock Market Simulation

Lecture 24 - Course Overview; What Do Computer Scientists Do?