Introduction to Computer Science and Programming (Spring 2011) (M-I-T)

• Lecture 1: Introduction to Computer Science and Programming (M-I-T)
• Recitation 1: Introduction to Coding Concepts (M-I-T)
• Lecture 3: Problem Solving (M-I-T)
• Lecture 4: Machine Interpretation of a Program (M-I-T)
• Recitation 2: Loops, Tuples, Strings, and Functions (M-I-T)
• Lecture 5: Objects in Python (M-I-T)
• Lecture 6: Recursion (M-I-T)
• Recitation 3: Lists and their Elements, Sorting, and Recursion (M-I-T)
• Lecture 7: Debugging (M-I-T)
• Recitation 4: Recursion, Pseudo code, and Debugging (M-I-T)
• Lecture 8: Efficiency and Order of Growth (M-I-T)
• Lecture 9: Memory and Search Methods (M-I-T)
• Lecture 10: Hashing and Classes (M-I-T)
• Lecture 11: Object Oriented Programming (OOP) and Inheritance (M-I-T)
• Recitation 5: Quiz 1 Answers and Object-Oriented Programming (M-I-T)
• Lecture 12: Introduction to Simulation and Random Walks (M-I-T)
• Optional Recitation: Algorithm Complexity and Class Review (M-I-T)
• Lecture 13: Some Basic Probability and Plotting Data (M-I-T)
• Lecture 14: Sampling and Monte Carlo Simulation (M-I-T)
• Lecture 15: Statistical Thinking (M-I-T)
• Recitation 6: Probability and Statistics (M-I-T)
• Lecture 16: Using Randomness to Solve Non-random Problems (M-I-T)
• Lecture 17: Curve Fitting (M-I-T)
• Recitation 7: Distributions, Monte Carlo, and Regressions (M-I-T)
• Lecture 18: Optimization Problems and Algorithms (M-I-T)