Computer Science 116
The Computational Universe

Spring 2008

Princeton University
Computer Science Department

General | Syllabus | Readings | Handouts | Assignments| Labs | Extras

Course Plan (tentative)

1: 2/5
  • Intro: Computer science, a new way of looking at the world. (CS is not just Programming!) [slides pdf/ppt]
  • Telling a robot how to behave. [slides pdf/ppt]
Web 2.0, Blogs, Social Networking [lab]
2: 2/12
  • Telling a computer how to behave. (Via pseudocode). [slides pdf/ppt]
  • Everything's a number. (Simulation. Creating new worlds. Games and Life.) [slides pdf/ppt]
Introduction to Pseudocode [lab]
3: 2/19
  • It ain't no good if it ain't snappy enough. (Efficient computations; viewing the world via efficiency.) [slides pdf/ppt]
  • "Seek and Ye shall find." (The continuum of computer "intelligence".) [slides pdf/ppt]
Controlling the Robot I [lab]
4: 2/26
  • It sure is clever, but can it swing? (Computer music.) [slides pdf/ppt]
  • What computers cannot do (I): The fluid boundary between program and data. [slides pdf/ppt]
Digital Audio and Music [lab]
5: 3/4
  • What computers cannot do (II): Universal machines. [slides pdf/ppt]
  • Ruminations on illumination (computer graphics). [slides pdf/ppt]
    • About self reproducing programs [pdf]
Controlling the Robot II [lab]
6: 3/11
  • Logic: From Greeks to philosophers to circuits. [slides pdf/ppt]
  • Midterm.
Review Session
- 3/18 -
  • ===== SPRING BREAK =====
7: 3/25
  • Memory, sequential and clocked circuits; Finite state machines. [slides pdf/ppt]
  • Computer organization: CPUs and RAM. [slides pdf/ppt]
Digital Logic I [lab]
8: 4/1
  • How to streamline your life (Lessons from computer architecture). [slides pdf/ppt]
  • What computers talk about and how. (Networking & the Internet.) [slides pdf/ppt]
Digital Logic II [lab]
9: 4/8
  • The science that drives modern computers. [slides pdf/ppt]
  • Viruses, worms, zombies, and other beasties. [slides pdf/ppt]
Internet Structure and Congestion Control [lab]
10: 4/15
  • What is the computational cost of automating brilliance or serendipity? (P vs NP question and related musings) [slides pdf/ppt]
  • Secrets and Lies, Knowledge and Trust. (Modern cryptography.) [slides pdf/ppt]
Virus and Worm Propagation in Networks [lab]
11: 4/22
  • Computer Vision and Graphics: Two sides of a coin [slides pdf/ppt]
  • Self-improvement for dummies(Machine Learning) [slides pdf/ppt]
Computer Graphics [lab]
12: 4/39
  • Artificial intelligence (and Searle's objection) [slides pdf/ppt]
  • What we have learnt in this course [slides pdf/ppt]
Machine Learning [lab]