Graduate classes, Spring 2016, Computer Science

CS 572: Information RetrievalCredits: 3− Description− Sections
Content: TBA
Texts: Information Retrieval by BŁttcher, Clarke and Cormack ISBN: 9780262026512
Assessments: TBA
Prerequisites: TBA
000MSC: W301MW 11:30am - 12:45pmEugene Agichteinmax 20
CS 580: Operating SystemsCredits: 3− Description− Sections
Content: The structure and organization of computer operating systems. Process, memory, and I/O management; device drivers, inter-machine communication, introduction to multiprocessor systems. An important portion of the course is a course long programming project that implements a simple operating system in stages. Each stage takes about three weeks, and is used as a basis for the next stage.
Texts: Operating System Concepts by Silbershatz ISBN: 9781118063330
Assessments: TBA
Prerequisites: TBA
000MSC: E408TuTh 2:30pm - 3:45pmKen Mandelbergmax 11
CS 584R: Topics in Computer Science: Advanced Computer SystemsCredits: 3− Description− Sections
Content: This course will cover seminal recent research papers across topics in distributed computer systems, with a focus on managing big data. Topics may include communication paradigms, process management, naming, synchronization, consistency and replication, fault tolerance, storage architectures, high-performance file systems, data provenance, and next-generation storage devices and architectures, including those at Google, Yahoo, and Amazon. Throughout the course, we will discuss the tradeoffs made between performance, reliability, scalability, robustness, and security. Students will be expected to critically read scientific papers, present at least 2 papers during the semester, and complete and present a final project.
Texts: Principles of Computer Sysytem Design: An Introduction by Saltzer & Kaashoek ISBN: 9780123749574. Guide to Reliable Distributed Systems: Building High-Assurance Applications and Cloud-Hosted Services by Birman ISBN: 9781447124153.
Assessments: TBA
Prerequisites: TBA
000MSC: W306TuTh 11:30am - 12:45pmAvani Wildanimax 20
CS 584R: Topics in Computer Science: mHealth InformaticsCredits: 3− Description− Sections
Content: TBA
Texts: None
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00PTBDTh 2:00pm - 5:00pmGari Cliffordmax 16
CS 584R: Topics in Computer Science: HPC + DACredits: 3− Description− Sections
Content: This course will introduce students to the fundamentals of high performance computing. We will first go over the fundamental concepts of parallel programming, current computing and networking architectures. You will learn about common parallel programming frameworks such as OpenMP and MPI. Issues such as performance monitoring, load balancing and communication will be addressed. You will also examine the Map Reduce programming model. Finally, if our schedule allows it, we will explore Apache Spark and/or Stream Programming. Along the way, we will review practical applications of the various technologies and models that we cover. This course will place a strong emphasis on the practice and implementation. To this end, I will try to make this a very hands-on course, with 3-4 programming assignments and a final project at the end of the course. Students who have code/applications, that they want to parallelize, are encouraged to use it as their final project.
Texts: Handouts, Class Readings, Programming Assignments, and a Final Project
Assessments: TBA
Prerequisites: TBA
002PAIS 561MW 4:00pm - 5:15pmAshish Sharmamax 20
CS 584R: Topics in Computer Science: Big Data AnalyticsCredits: 3− Description− Sections
Content: The course covers scalable machine learning and data mining algorithms for large/complex data. Topics include large-scale optimization techniques, hashing, recommendation systems, and tensor factorization. This will be structured as a seminar course with emphasis on public data sets such as Kaggle competitions, MovieLens, and various healthcare datasets. The instructor will provide introductory lectures that set the context and provide reviews of relevant material.
Texts: Mining of Massive Datasets by Leskovec, Rajaraman and Ullman ISBN: 9781107077232. Data Just Right: Introduction to Large-Scale Data & Analytics by Manoochehri ISBN: 9780321898654. Data Science from Scratch: First Principles with Python by Grus ISBN: 9781491901427
Assessments: TBA
Prerequisites: Graduate Data Mining (CS 570) and familiarity with Python, Matlab, or R.
001MSC: W303MW 2:30pm - 3:45pmJoyce Homax 20
CS 597R: Directed StudyCredits: 1 - 9− Description− Sections
Content: TBA
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00PMSC: -----Faculty (TBA)max 999
CS 598R: Rotation ProjectCredits: 1 - 3− Description− Sections
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00PMSC: -----Faculty (TBA)max 0
CS 599R: Master's Thesis ResearchCredits: 1 - 9− Description− Sections
Content: TBA
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VIGFMSC: -----Faculty (TBA)max 0
CS 700R: Graduate SeminarCredits: 1− Description− Sections
Content: This is a required course for all students in the PhD program. It comprises seminars given by faculty, invited guests, and students.
Texts: TBA
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000MSC: W301F 3:00pm - 3:50pmVaidy Sunderammax 30
CS 797R: Directed StudyCredits: 1 - 9− Description− Sections
Content: TBA
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CS 799R: Dissertation ResearchCredits: 1 - 9− Description− Sections
Content: TBA
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00PMSC: -----Faculty (TBA)max 999