|
|
|
|
|
|
|
|
|
|
Course Criteria
Add courses to your favorites to save, share, and find your best transfer school.
-
1.00 Credits
Applications of Probabilistic Graphical Models in Language and Speech Processing Probabilistic graphical models (PGMs) combine ideas from statistics and computer science into a unifying framework for modeling complex real-world phenomena. PGMs are now widespread in language and speech processing. PGMs are well suited to handle the inherent challenges of linguistic problems: complex and structured relationships, a large number of relevant attributes, and large volumes of data. This short course will provide students with advanced training in several specific applications of graphical models that are important in natural language processing. After reviewing the essentials of directed and undirected graphical models, we will discuss complex CRFs, approximate inference including variational and MCMC methods, Bayesian models and non-parametric Bayesian models including Chinese Restaurant Processes. Students will also gain practical experience by solving problems using existing PGM software. Recommended Prerequisite: 600.465. Short course.
-
1.00 Credits
This course focuses on the security and privacy issues in Cloud Computing systems. While the cloud computing paradigm gains more popularity, there are many issues related to confidentiality, integrity, and availability of data and computations involving a cloud. In this course, we examine cloud computing models, look into the threat model and security issues related to data and computation outsourcing, and explore practical applications of secure cloud computing. Short course. Prereqs: Some background in network and/or data security recommended.
-
3.00 Credits
Data stream processing has emerged as a model for building computing applications that face tremendous volumes of dynamically changing data, and are required to process such data in a timely fashion. Examples include a variety of web-driven applications, such as web advertising based on Facebook and Twitter status streams, and more generally, monitoring and analysis applications including algorithmic trading on stock ticks and order books, network monitoring for denial of service attacks, and location-based applications working with GPS data streams. This course will study data stream processing from a data management and algorithms perspective. Students will be introduced to the fundamentals of data stream processing systems and architectures, incremental (windowed) stream processing languages, and stream algorithms that embody the principle of "you only get one look" when having to continually deal with data arriving at high rates. This course will provide students with significant implementation experience, in the spirit of a practicum. Students will proceed through a series of homework projects to build a data stream processor from scratch, and will use the resulting stream engine along with stream mining algorithms to analyze Twitter feeds. This course is aimed at upper-level undergraduates with prior programming experience. Graduate students should consider taking 600.617 instead. Students may receive credit for 600.417 or 600.617, but not both. [Systems] Pre-reqs: 600.120, 600.226, and 600.315/415.
-
3.00 Credits
Prereq: 600.226, and 600.333; 600.211 recommended. Students may receive credit for 600.318 or 600.418, but not both. Graduate level version of 600.318. [Systems]
-
3.00 Credits
This course focuses on communication security in computer systems and networks. The course is intended to provide students with an introduction to the field of network security. The course covers network security services such as authentication and access control, integrity and confidentiality of data, firewalls and related technologies, Web security and privacy. Course work involves implementing various security techniques. A course project is required. Prerequisites: 600.226, 600.344/444 or permission; 600.120 (or equivalent) recommended. [Systems]
-
3.00 Credits
Prereq: 600.226, 600.271, Calc II. Students can only receive credit for 600.325 or 600.425, not both. Graduate level version of 600.325. [Analysis]
-
3.00 Credits
No Freshmen or Sophomores Prereq: 600.226 Functional, object-oriented, and other language features are studied independent of a particular programming language. Students become familiar with these features by implementing them. Most of the implementations are in the form of small language interpreters. Some type checkers and a small compiler will also be written. The total amount of code written will not be overly large, as the emphasis is on concepts. The ML programming language is the implementation language used. [Analysis]
-
3.00 Credits
This course will examine the complex relationship between computer architectures and software systems that store, organize, and access data. Storage systems have always co-evolved with technology. But, today's computing landscape places unique demands on next generation storage systems. Technology drivers include: new storage devices, such as solid-state drives and phase-change memory, cloud computing, virtualization, and modern multicore and manycore processors with steep hierarchies of shared caches. The course will provide an overview of modern storage systems, including parallel file systems, key/value stores, scan engines, in-memory databases, archival storage, and content-based storage. It will cover the techniques used to organize storage in these systems, such as indexes, replication and coding, spatial trees, and space-filling curves. The course will also explore external memory data structures and algorithms that provide a framework for analyzing storage designs. [Systems] Pre-reqs: 600.226, 600.315/415, and 600.333/433 or permission of instructor.
-
3.00 Credits
Graduate version of 600.328. Students may receive credit for 600.328 or 600.428, but not both. Prereqs: C/C++ programming and data structures Introduction to compiler design, including lexical analysis, parsing, syntax-directed translation, symbol tables, run-time environments, and code generation and optimization. Students are required to write a compiler as a course project.[Systems] Co-listed with 600.328
-
3.00 Credits
Prerequisites: 600.107 or 600.109. This course is the graduate-level version of 600.333. Students may receive credit for 600.333 or 600.433, but not both.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Privacy Statement
|
Cookies Policy |
Terms of Use
|
Institutional Membership Information
|
About AcademyOne
Copyright 2006 - 2025 AcademyOne, Inc.
|
|
|