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Fall 2014 Undergraduate & Graduate Special Topic Courses

CSC495/591-001 Spoken Dialogue Systems - Dr. Boyer

Prerequisites: CSC316

Computers that understand and generate speech are the way of the future, and are an increasingly important part of daily life (for example, Apple's Siri). Because of this, knowledge and skills related to how computers understand and generate natural language are increasingly in demand. In fact, Natural Language Speech Scientist has been rated as one of the five hottest computing jobs over the next five years. In this course, we will learn step-by-step how spoken dialogue systems are created. Beginning with automatic speech recognition and generation, continuing through natural language understanding techniques such as grammars and parsing, then moving on to dialogue management and domain modeling, students will leave the course with a broad understanding of natural language and speech concepts and technologies. Applying what is learned in class, students will work in teams to build a working dialogue system by combining existing toolkits with their own implementations. The course features an undergraduate (CSC 495) and a graduate track (CSC 591), each with its own project and exam requirements to ensure that the content is appropriate for both academic levels. At the completion of the class, students will have a broad set of knowledge and skills that they can apply in any situation that involves processing natural language.


CSC 495-002 Data Sciences - Dr. Avent, Dr. Wilson

Prerequisites:

  • Knowledge of linear algebra at the undergraduate level (MA 305 or MA 405)
  • Knowledge of statistics at the undergraduate level (STAT 305, 312, 370, or 372)
  • Programming in any language like Python, C++, FORTRAN, or Java (CSC 112, 114, or 116)
  • Programming in R, SAS, or Matlab is desirable but not required.

Data Science has become increasingly important in nearly every industry sector and academic field. It has gained significant national attention and interest by combining techniques from several fields like Computer Science, Statistics, and Mathematics to extract knowledge from data. This course provides an overview of several foundational topics in Data Science and will expose students to the theory and algorithms underlying these techniques, as well as the use of commercial software packages. The class will include a mix of lectures and programming projects.


CSC591-027 Network Design and Management - Dr. Viniotis

This course will expose students to the fundamental issues that arise in the design and management of computer networks, with special emphasis on campus enterprise networks. Such issues include, among others: business objectives and technical design requirements, VLAN network design, data center network design, and SOHO network design. We will outline available methods and tools for designing, operating and managing such networks. Such methods include, among others: virtualization, automation and consolidation. We will provide the students with practical experience on available tools in the network design and management space. In-class demos and (a series of 4-6) lab demos will be used for that purpose; we use open source tools (such as openNMS) as well as commercial tools (such as IBM Tivoli’s Netcool and Cisco’s Prime.)

Network design and management is a broad, multi-semester topic. The material covered in this course is selected to help the students pass the Cisco 642-813 Certification exam. This exam is the first step towards CCNP (Switch), CCDA and CCDP certifications.