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6.00SC Introduction to Computer Science and Programming

6.00SC Introduction to Computer Science and Programming (Spring 2011, MIT OCW). Instructor: 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 23 - Dynamic Programming

This lecture introduces dynamic programming, and discusses the notions of optimal substructure and overlapping subproblems.

References

Dynamic Programming | Unit 3
Resources: Lecture code handout (PDF); Lecture code (PY). Check Yourself.

Go to the Course Home or watch other lectures:

Unit 1

Lecture 01 - Introduction to 6.00

Lecture 02 - Core Elements of a Program

Lecture 03 - Problem Solving

Lecture 04 - Machine Interpretation of a Program

Lecture 05 - Objects in Python

Lecture 06 - Recursion

Lecture 07 - Debugging

Lecture 08 - Efficiency and Order of Growth

Lecture 09 - Memory and Search Methods

Unit 2

Lecture 10 - Hashing and Classes

Lecture 11 - OOP and Inheritance

Lecture 12 - Introduction to Simulation and Random Walks

Lecture 13 - Some Basic Probability and Plotting Data

Lecture 14 - Sampling and Monte Carlo Simulation

Lecture 15 - Statistical Thinking

Lecture 16 - Using Randomness to Solve Non-random Problems

Lecture 17 - Curve Fitting

Lecture 18 - Optimization Problems and Algorithms

Lecture 19 - More Optimization and Clustering

Unit 3

Lecture 20 - More Clustering

Lecture 21 - Using Graphs to Model Problems, Part 1

Lecture 22 - Using Graphs to Model Problems, Part 2

Lecture 23 - Dynamic Programming

Lecture 24 - Avoiding Statistical Fallacies

Lecture 25 - Queuing Network Models

Lecture 26 - What Do Computer Scientists Do?