CPSC 201: Introduction to Computer Science

Instructor: Carsten Schürmann
Department of Computer Science
Yale University
Time: MWF 11:30-12:20
Room: AKW200

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Schedule

Lecture 1: What is Computer Science? Why ML?

Lecture 2: Binding, Scope, and Functions.

Lecture 3: Functions, Products, and Records.

Lecture 4: Datatypes and Pattern Matching.

Lecture 5: Recursion and Induction.

Lecture 6: Recursive Datatypes.

Lecture 7: Lists.

Lecture 8: Boolean functions.

Lecture 9: Boolean algebra/circuits.

Lecture 10: Integers, floating point numbers ..., (PDF)

Lecture 11: Adders, (PDF)

Lecture 12: Sequential Circuits, (PDF)

Lecture 13: Lazy data structures, (PDF)

Lecture 14: Hands-on experience with SML.

Lecture 15: Lazy data structures continued.

Lecture 16: The von Neumann machine.

Lecture 17: Programming with machine code.

Lecture 18: A machine code simulator.

Lecture 19: The lambda-calculus.

Lecture 20: Midterm.

Lecture 21: Turing Machines.

Lecture 22: Porgraming on Turing machines.

Lecture 23: Midterm Review.

Lecture 24: The Halting Problem.

Lecture 25: Regular Languages.

Lecture 26: Regular Akzeptors.

Lecture 27: Lexer.

Lecture 28: Parser.

Lecture 29: Interpreters.

Lecture 30: Artificial Intelligence.

Lecture 31: Search.

Lecture 32: More on Search.

Lecture 33: The Module System of SML.

Lecture 34: Algorithmic Methods

Lecture 35: Efficieny of algorithms

Lecture 36: Intractability

Lecture 37: P vs NP.

Lecture 38: NP completeness.

Lecture 39: Review and summary.