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6.01SC Introduction to Electrical Engineering and Computer Science, I Spring 2011

6.01SC Introduction to Electrical Engineering and Computer Science, I Spring 2011

27 Videos · Jan 20, 2011

About

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.

Videos

Recitations

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16:28

Recitation 3: Python Notables

Kendra Pugh

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10:31

Recitation 11: Op-Amps

Kendra Pugh

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13:46

Recitation 4: State Machines

Kendra Pugh

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15:21

Recitation 8: Poles, Part II

Kendra Pugh

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15:13

Recitation 15: Search: Basics

Kendra Pugh

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11:22

Recitation 1: Object-Oriented Programming

Kendra Pugh

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13:25

Recitation 2: Inheritance

Kendra Pugh

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15:09

Recitation 6: System Equivalences

Kendra Pugh

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17:45

Recitation 9: Circuits: Representation, KVL, KCL

Kendra Pugh

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12:47

Recitation 5: LTI Motivations and Representations

Kendra Pugh

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15:27

Recitation 13: Probability: Basics

Kendra Pugh

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14:20

Recitation 16: Search: Dynamic Programming, Costs and Heuristics

Kendra Pugh

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13:50

Recitation 10: Circuits: NVCC, Sample Problem

Kendra Pugh

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12:18

Recitation 14: Probability: State Estimation

Kendra Pugh

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09:05

Recitation 7: Poles, Part I

Kendra Pugh

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12:40

Recitation 12: Thevenin/Norton Equivalence and Superposition

Kendra Pugh

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01:11:18

Lecture 9: Circuit Abstractions

Dennis Freeman

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01:17:34

Lecture 1: Object-Oriented Programming

Dennis Freeman

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01:14:53

Lecture 6: Designing Control Systems

Dennis Freeman

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01:18:30

Lecture 5: Characterizing System Performance

Dennis Freeman

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01:20:08

Lecture 2: Primitives, Combination, Abstraction, and Patterns

Dennis Freeman

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01:18:13

Lecture 7: Circuits

Dennis Freeman

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01:19:27

Lecture 8: Op-Amps

Dennis Freeman

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01:17:48

Lecture 10: Discrete Probability and State Estimation

Dennis Freeman

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01:08:05

Lecture 12: Search Algorithms

Dennis Freeman

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01:03:34

Lecture 13: Optimizing a Search

Dennis Freeman

calendar icon Feb 4, 2013 2506 views

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01:19:43

Lecture 3: Signals and Systems

Dennis Freeman

calendar icon Feb 4, 2013 5158 views

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