CSE 312: Foundations of Computing II, Spring 2014

[calendar | important announcements] | GoPost discussion board | course information | anonymous feedback | prior incarnations of course | acknowledgements

important announcements

• The final will be held in Kane 120
• Review session Sunday at 3:30pm in EEB 125; office hours Mon-Tues at 4:30 in CSE 220.
• Topics and reading for the final
• Here is the calendar for the course. Almost all information (such as lecture materials and assignments) is/will be linked from the calendar.
• To submit daily problems, you'll need to log in to the Catalyst Dropbox. There you will be able to submit your solution to the daily problem.
• Videos of lectures: from the fall incarnation in the course (bottom left of page) and from MIT (lectures 16 - 25)
• Quick guide for getting started with latex, a typesetting system that is very useful for typesetting mathematics.

course information

Lectures time and place: MWF 9:30-10:20am, in CMU 120
Sections time and place: AA: Thursday 12:30 -- 1:20 in MEB 246; AB: Thursday 1:30 -- 2:20 in JHN 111; AC: Thursday 2:30 -- 3:20 in ART 317

Instructor: Anna Karlin, CSE 594, tel. 543 9344
Office hours: Tuesdays: 9-10am, Thursdays: 3:30 -4:30pm, CSE 594, and by appointment -- just send email.

Teaching assistants: Sonja Khan, Noah Siegel, Akshay Srinivasan, and Dylan Swiggett
Office hours: Mondays 4-5pm and Wednesdays 4:30-5:30pm and Thursdays 4:30-5:30pm in CSE 220 and by appointment.

Course evaluation and grading:

• Rough breakdown: Daily problems (5-10%), weekly problem sets (altogether 35-45%), midterm (15-20%) and final (30-35%).
• Daily problems will be graded as credit/no-credit, with credit received for a credible effort.
• Late homework will be accepted (but penalized 30%) up to Friday's class; not accepted thereafter, barring major emergencies. Late daily problems will not be accepted (but you have a pass on turning them in four times during the quarter).

Textbooks:

• [LLM] (free online) Mathematics for Computer Science, Lehman, Leighton and Meyer. (Chapters 15, 17-20).
• [DBC] (free online) OpenIntro Statistics, Dietz, Barr and Cetinkaya-Rundel.
• [BT] (optional) Introduction to Probability (2nd edition), Dimitri P. Bertsekas and John N. Tsitsiklis, Athena Scientific, 2008 (Available from U Book Store, Amazon, etc.) Online version 1st edition
• [R] (optional) Kenneth H. Rosen, Discrete Mathematics and Its Applications, Sixth Edition, McGraw-Hill, 2007. No direct use of this, but if you already own a copy, keep it for reference. Some students have said they like its coverage of counting (Chapter 5 and 7.5, 7.6) and discrete probability (Chapter 6)).

Learning Objectives:

Course goals include an appreciation and introductory understanding of (1) methods of counting and basic combinatorics, (2) the language of probability for expressing and analyzing randomness and uncertainty (3) properties of randomness and their application in designing and analyzing computational systems, (4) some basic methods of statistics and their use in a computer science & engineering context.

The mailing list (cse312a_sp14@uw.edu) is used to communicate important information that is relevant to all the students. If you are registered for the course, you should automatically be on the mailing list.

Homeworks are all individual, not group, exercises. Discussing them with others is fine, even encouraged, but you must produce your own homework solutions. Follow the "Gilligan's Island Rule": if you discuss the assignment with someone else, don't keep any notes (paper or electronic) from the discussion, then go watch 30+ minutes of TV (Gilligan's Island reruns especially recommended) before you continue work on the homework by yourself. You may not look at other people's written solutions to these problems, not in your friends' notes, not in the dorm files, not on the internet, ever. If in any doubt about whether your activities cross allowable boundaries, tell us before, not after, you turn in your assignment. See also the UW CSE Academic Misconduct Policy, and the links there.

acknowledgements

Thanks to previous instructors of this course (James Lee, Larry Ruzzo, Martin Tompa and Pedro Domingos) for the use of their slides and other materials. (Some of these were in turn drawn from other sources.) We have also drawn on materials from "Mathematics for Computer Science" at MIT, and "Great Theoretical Ideas in Computer Science" at CMU, from Edward Ionides at the University of Michigan, and from an offering of CS 70 at Berkeley by Tse and Wagner.