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CS 252.00 Algorithms 6 credits

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

Anderson Hall 329

MTWTHF
11:10am12:20pm11:10am12:20pm12:00pm1:00pm
Synonym: 64314

Eric C Alexander

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 314.00 Data Visualization 6 credits

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

Weitz Center 235

MTWTHF
1:50pm3:00pm1:50pm3:00pm2:20pm3:20pm
Synonym: 64318

Eric C Alexander

Understanding the wealth of data that surrounds us can be challenging. Luckily, we have evolved incredible tools for finding patterns in large amounts of information: our eyes! Data visualization is concerned with taking information and turning it into pictures to better communicate patterns or discover new insights. It combines aspects of computer graphics, human-computer interaction, design, and perceptual psychology. In this course, we will learn the different ways in which data can be expressed visually and which methods work best for which tasks. Using this knowledge, we will critique existing visualizations as well as design and build new ones.

Prerequisite: Computer Science 201

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You must take 6 credits of each of these.
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You must take 6 credits of each of these,
except Quantitative Reasoning, which requires 3 courses.
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