Lecture 1: Overview. Abstractions. ML.
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Lecture 2: Datatypes, source code.
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Lecture 3: Functions, source code.
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Lecture 4: Recursion and Pattern Matching, source code.
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Lecture 5: More on Pattern Matching, Lists, source code.
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Lecture 6: Abstract Data Types, Signatures and Structures, source code.
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Lecture 7: Physics and Transistors.
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Lecture 8: Boolean algebra, Boolean Expressions, source code.
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Lecture 9: Gates and Circuits.
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Lecture 10: Circuit Simulation, source code.
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Lecture 11: Adders, (PDF)
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Lecture 12: Sequential Circuits, (PDF)
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Lecture 13: Lazy data structures, (PDF)
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Lecture 14: Hands-on experience with SML.
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Lecture 15: Lazy data structures continued.
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Lecture 16: The von Neumann machine.
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Lecture 17: Programming with machine code.
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Lecture 18: A machine code simulator.
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Lecture 19: The lambda-calculus.
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Lecture 20: Midterm.
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Lecture 21: Turing Machines.
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Lecture 22: Porgraming on Turing machines.
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Lecture 23: Midterm Review.
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Lecture 24: The Halting Problem.
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Lecture 25: Regular Languages.
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Lecture 26: Regular Akzeptors.
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Lecture 27: Lexer.
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Lecture 28: Parser.
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Lecture 29: Interpreters.
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Lecture 30: Artificial Intelligence.
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Lecture 31: Search.
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Lecture 32: More on Search.
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Lecture 33: The Module System of SML.
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Lecture 34: Algorithmic Methods
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Lecture 35: Efficieny of algorithms
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Lecture 36: Intractability
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Lecture 37: P vs NP.
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Lecture 38: NP completeness.
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Lecture 39: Review and summary.
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