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CS 631Data-Intensive Distributed Analytics

Units
0.50
Level
Graduate
Faculty
Mathematics
Subject
Computer Science

CS 631 as listed in the Winter 2025 Graduate Calendar. The main page has the current version, when it runs, and seats.

Introduces non-CS major students to infrastructure for data-sensitive analytics, with a focus on abstractions, frameworks, and algorithms that allow developers to distribute computations across many machines. Topics include core concepts (partitioning, replication, locality, consistency), computational models (MapReduce, dataflows, stream processing, bulk-synchronous parallel), and applications.

Prerequisites

None listed.

Antirequisites

None listed.

Leads to

No course lists it as a requisite.

Check it elsewhere for Winter 2025

Calendar versions

Graduate Calendar

Older Graduate Calendars

In 13 terms, Winter 2020 to Winter 2024