ENROLL Course Search

NOTE: There are some inconsistencies in the course listing data - ITS is looking into the cause.

Alternatives: For requirement lists, please refer to the current catalog. For up-to-the-minute enrollment information, use the "Search for Classes" option in The Hub. If you have any other questions, please email registrar@carleton.edu.

Saved Courses (0)

Your search for courses for 19/WI found 2 courses.

Revise Your Search New Search

CS 252.00 Algorithms 6 credits

Closed: Size: 34, Registered: 34, Waitlist: 0

CMC 301

MTWTHF
8:30am9:40am8:30am9:40am8:30am9:30am

Requirements Met:

Other Tags:

Synonym: 52720

David Liben-Nowell

A course on techniques used in the design and analysis of efficient algorithms. We will cover several major algorithmic design paradigms (greedy algorithms, dynamic programming, divide and conquer, and network flow). Along the way, we will explore the application of these techniques to a variety of domains (natural language processing, economics, computational biology, and data mining, for example). As time permits, we will include supplementary topics like randomized algorithms, advanced data structures, and amortized analysis.

Prerequisite: Computer Science 201 and Computer Science 202 (Mathematics 236 will be accepted in lieu of Computer Science 202)

CS 352.00 Advanced Algorithms 6 credits

Open: Size: 34, Registered: 25, Waitlist: 0

Leighton 330

MTWTHF
11:10am12:20pm11:10am12:20pm12:00pm1:00pm

Requirements Met:

Other Tags:

Synonym: 51323

David Liben-Nowell

A second course on designing and analyzing efficient algorithms to solve computational problems. We will survey some algorithmic design techniques that apply broadly throughout computer science, including discussion of wide-ranging applications. A sampling of potential topics: approximation algorithms (can we efficiently compute near-optimal solutions even when finding exact solutions is computationally intractable?); randomized algorithms (does flipping coins help in designing faster/simpler algorithms?); online algorithms (how do we analyze an algorithm that needs to make decisions before the entire input arrives?); advanced data structures; complexity theory. As time and interest permit, we will mix recently published algorithmic papers with classical results.

Prerequisite: Computer Science 252 or instructor permission

Search for Courses

This data updates hourly. For up-to-the-minute enrollment information, use the Search for Classes option in The Hub

Instructional Mode
Class Period
Courses or labs meeting at non-standard times may not appear when searching by class period.
Requirements
You must take 6 credits of each of these.
Overlays
You must take 6 credits of each of these,
except Quantitative Reasoning, which requires 3 courses.
Special Interests