CSCI 421 - Computer Science Theory Topics Seminar

This course is an exploration of research in an area of theoretical computer science. Topics vary by offering. Prerequisites vary by topic. Example topics include randomized or parallel algorithms, approximation algorithms, quantum computation or complexity, and zero-knowledge proof systems. Not all topics offered every year.

Distributed Consensus
An introduction to distributed consensus algorithms. Topics include classical algorithms and lower bounds, permissionless consensus and cryptocurrencies, and state machine replication. The course emphasizes engaging directly with published research and building written and oral communication skills.

Unit(s): 0.5
Group Distribution Requirement(s): Distribution Group III
Prerequisite(s): Distributed Consensus: CSCI 382 or MATH 382
Instructional Method: Lecture-conference
Grading Mode: Letter grading (A-F)
Repeatable for Credit: May be taken 4 times for credit
Cross-listing(s): MATH 421
Group Distribution Learning Outcome(s):

Use and evaluate quantitative data or modeling, or use logical/mathematical reasoning to evaluate, test or prove statements.
Given a problem or question, formulate a hypothesis or conjecture, and design an experiment, collect data, or use mathematical reasoning to test or validate it.