Introduction to Electrical Engineering & Computer Science (M-I-T)

• Lecture 1: Object-Oriented Programming (M-I-T)
• Recitation 1: Object-Oriented Programming (M-I-T)
• Recitation 2: Inheritance (M-I-T)
• Lecture 2: Primitives, Combination, Abstraction, and Patterns (M-I-T)
• Recitation 3: Python Notables (M-I-T)
• Recitation 4: State Machines (M-I-T)
• Lecture 3: Signals and Systems (M-I-T)
• Recitation 5: LTI Motivations and Representations (M-I-T)
• Recitation 6: System Equivalences (M-I-T)
• Lecture 5: Characterizing System Performance (M-I-T)
• Recitation 7: Poles, Part I (M-I-T)
• Recitation 8: Poles, Part II (M-I-T)
• Lecture 6: Designing Control Systems (M-I-T)
• Lecture 7: Circuits (M-I-T)
• Recitation 9: Circuits: Representation, KVL, KCL (M-I-T)
• Recitation 10: Circuits: NVCC, Sample Problem (M-I-T)
• Lecture 8: Op-Amps (M-I-T)
• Lecture 9: Circuit Abstractions (M-I-T)
• Recitation 12: Thevenin/Norton Equivalence and Superposition (M-I-T)
• Lecture 10: Discrete Probability and State Estimation (M-I-T)
• Recitation 13: Probability: Basics (M-I-T)
• Recitation 14: Probability: State Estimation (M-I-T)
• Lecture 12: Search Algorithms (M-I-T)
• Recitation 15: Search: Basics (M-I-T)
• Lecture 13: Optimizing a Search (M-I-T)