Special Topics in Computer Science
COMP 360A
Fall 2017
| Section:
01
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This course covers special topics in computer science. Topics will vary according to the instructor. |
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| Credit: 1 |
Gen Ed Area Dept:
NSM MATH |
| Course Format: Lecture | Grading Mode: Graded |
| Level: UGRD |
Prerequisites: COMP212 AND MATH228 |
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Fulfills a Requirement for: None |
| SECTION 01 |
Major Readings: Wesleyan RJ Julia Bookstore
To be announced.
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Examinations and Assignments:
TBA |
Additional Requirements and/or Comments:
Randomization and probabilistic analysis have become fundamental tools in modern Computer Science, with applications ranging from network security, cryptography and communication protocols to web search, computational finance and data mining. This course introduces the basic probabilistic techniques used in computer science applications, in particular covering the following topics:
1. randomized algorithms (such as randomized QuickSort)
2. probabilistic analysis of algorithms (such as expected time
complexity)
3. statistical inference methods (such as Markov Chain Monte Carlo
methods)
Prior knowledge of discrete probability theory is encouraged but not required, as we will cover the basic probability theory (including probability spaces, events, random variables, expectation, etc) required for our purposes. Programming assignments can be done u! sing Python, Java, C/C++ or R. |
| Instructor(s): Shai,Saray Times: .M.W... 01:20PM-02:40PM; Location: SCIE139; |
| Total Enrollment Limit: 19 | | SR major: 8 | JR major: 8 | | |
| | GRAD: X | SR non-major: 0 | JR non-major: 0 | SO: 3 | FR: 0 |
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