### 6.01SC Introduction to Electrical Engineering and Computer Science I

**6.01SC Introduction to Electrical Engineering and Computer Science I (Spring 2011, MIT OCW)**. Taught by Professor Dennis Freeman, this course provides
an integrated introduction to electrical engineering and computer science, taught using substantial laboratory experiments with mobile robots. Our primary goal is
for you to learn to appreciate and use the fundamental design principles of modularity and abstraction in a variety of contexts from electrical engineering and
computer science. Our second goal is to show you that making mathematical models of real systems can help in the design and analysis of those systems. Finally,
we have the more typical goals of teaching exciting and important basic material from electrical engineering and computer science, including modern software engineering,
linear systems analysis, electronic circuits, and decision-making.
(from **ocw.mit.edu**)

Lecture 10 - Discrete Probability and State Estimation |

In this unit, we'll address the problem that systems we design may have to operate under uncertainty, and that we may want those systems to be able to search the world for possible solutions to problems. We'll introduce the basics of probability and search in this session, and apply those concepts to our design challenges.

References |

Discrete Probability | Unit 4Readings. Lecture handout (PDF). Lecture slides (PDF). Recitation Videos. Session Activities. |

State Estimation | Unit 4Readings. Recitation Videos. Session Activities. Check Yourself. |

Go to **the Course Home** or watch other lectures:

Unit 1: Software Engineering |

Lecture 01 - Object-oriented Programming |

Lecture 02 - Primitives, Combination, Abstraction, and Patterns |

Unit 2: Signals and Systems |

Lecture 03 - Signals and Systems |

Lecture 04 |

Lecture 05 - Characterizing System Performance |

Lecture 06 - Designing Control Systems |

Unit 3: Circuits |

Lecture 07 - Circuits |

Lecture 08 - Op-Amps |

Lecture 09 - Circuit Abstractions |

Unit 4: Probability and Planning |

Lecture 10 - Discrete Probability and State Estimation |

Lecture 11 |

Lecture 12 - Search Algorithms |

Lecture 13 - Optimizing a Search |