Learn · Introduction to Electrical Engineering and Computer Science I
Lecture 1 of 54Object-Oriented Programming1 h 18 min
Lecture 1: Object-Oriented Programming
Prof. Leslie Kaelbling and others · Massachusetts Institute of Technology
Credits and licence
- From
- Introduction to Electrical Engineering and Computer Science I, Massachusetts Institute of Technology (at MIT OpenCourseWare)
- Licence
- CC BY-NC-SA 4.0, as MIT OpenCourseWare states it. Non-commercial use only.
- Attribution
- Prof. Leslie Kaelbling, Prof. Jacob White, Prof. Harold Abelson, Prof. Dennis Freeman, Prof. Tomás Lozano-Pérez, Prof. Isaac Chuang. Introduction to Electrical Engineering and Computer Science I. Spring 2011. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu/. License: Creative Commons BY-NC-SA.
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- Tweens profiles and older. How courses are placed
All the lectures
- Lecture 1: Object-Oriented Programming
- Recitation 1: Object-Oriented Programming
- Recitation 2: Inheritance
- Lecture 2: Primitives, Combination, Abstraction, and Patterns
- Recitation 3: Python Notables
- Recitation 4: State Machines
- Lecture 3: Signals and Systems
- Recitation 5: LTI Motivations and Representations
- Recitation 6: System Equivalences
- Lecture 5: Characterizing System Performance
- Recitation 7: Poles, Part I
- Recitation 8: Poles, Part II
- Lecture 6: Designing Control Systems
- Lecture 7: Circuits
- Recitation 9: Circuits: Representation, KVL, KCL
- Recitation 10: Circuits: NVCC, Sample Problem
- Lecture 8: Op-Amps
- Recitation 11: Op-Amps
- Lecture 9: Circuit Abstractions
- Recitation 12: Thevenin/Norton Equivalence and Superposition
- Lecture 10: Discrete Probability and State Estimation
- Recitation 13: Probability: Basics
- Recitation 14: Probability: State Estimation
- Lecture 12: Search Algorithms
- Recitation 15: Search: Basics
- Lecture 13: Optimizing a Search
- Recitation 16: Search: Dynamic Programming, Costs and Heuristics
- Lecture 1: Object-Oriented Programming
- Recitation 1: Object-Oriented Programming
- Recitation 2: Inheritance
- Lecture 2: Primitives, Combination, Abstraction, and Patterns
- Recitation 3: Python Notables
- Recitation 4: State Machines
- Lecture 3: Signals and Systems
- Recitation 5: LTI Motivations and Representations
- Recitation 6: System Equivalences
- Lecture 5: Characterizing System Performance
- Recitation 7: Poles, Part I
- Recitation 8: Poles, Part II
- Lecture 6: Designing Control Systems
- Lecture 7: Circuits
- Recitation 9: Circuits: Representation, KVL, KCL
- Recitation 10: Circuits: NVCC, Sample Problem
- Lecture 8: Op-Amps
- Recitation 11: Op-Amps
- Lecture 9: Circuit Abstractions
- Recitation 12: Thevenin/Norton Equivalence and Superposition
- Lecture 10: Discrete Probability and State Estimation
- Recitation 13: Probability: Basics
- Recitation 14: Probability: State Estimation
- Lecture 12: Search Algorithms
- Recitation 15: Search: Basics
- Lecture 13: Optimizing a Search
- Recitation 16: Search: Dynamic Programming, Costs and Heuristics