Page 190 - University Bulletin

CS476 Natural Language Processing
Credits: 3(3,0,1) Prerequisites: CS316
The course is about natural language processing – representation, parsing, natural language
generation, and the interaction between long-term knowledge and understanding with a focus on
Arabic language processing.

CS481 Big Data Analytics
Credits: 3(3,0,1) Prerequisites: CS316
This course harnesses the power of large-scale data in various domains. The course takes a
practical approach, focusing on the technologies and techniques used to create Big Data Analytics
applications. Students will learn about NoSQL big data management and how to use MapReduce
analytics using Hadoop and related tools. They will work with map reduce applications and
understand the usage of Hadoop related tools for Big Data Analytics. By the end of the course,
students will be able to design, implement, and evaluate Big Data Analytics solutions using various
technologies and tools. The course will have a strong practical component, with students working
on real-world projects and case studies to apply the concepts and techniques learned in the
course. By the end of the course, students will have gained the knowledge and skills necessary to
work with large-scale data and contribute to the development of innovative Big Data Analytics
applications.

CS489 Selected Topics in Computer Science
Credits: 3(3,0,1) Prerequisites: CS210 and Department consent
This course covers topics in the computer science discipline not covered by other CS courses.
Students are encouraged to propose topics for this course.

CS492 Cooperative Education (Co-op)
Credits: 10 Prerequisites: Department consent
The Co-op is a career related professional program available to all Computer Science students. It
is designed to help students build on skills already learned in the classroom and acquire new ones
as well. Co-op education is available to CCIS students who have accumulated the requisite number
or more credits. The Co-op option counts for 10 credit hours (CRs) for practical onsite experience
over a 7 month period, i.e. spanning one semester and a summer.

CS495 Emerging Topics in Computer Science
Credits: 3(3,0,1) Prerequisites: Department consent
This course covers topics in the computer science discipline that recently gained innovative
attention in Computer Science. Students are encouraged to propose topics for this course.

CS496 Emerging Topics in Artificial Intelligence and Data Science
Credits: 3(3,0,1) Prerequisites: Department consent
This course covers topics in the AI and DS discipline that recently gained innovative attention in
Computer Science. Students are encouraged to propose topics for this course.

CS499 Senior Project
Credits: 3(3,0,0) Prerequisites: Completion of 88 credit hours + Department Consent
This course provides students with an opportunity to integrate their academic work into the
design and development of a significant computing product that showcases the students’ skills.
Students are expected to work in teams addressing problems and challenges from the real world
and develop appropriate computing-based solutions. Students would complete the senior project
addressing the documentation, development, implementation, testing, experimental evaluation,
and deployment phases of their work. The final project would be demonstrated to an audience.

178 PSU UNDERGRADUATE BULLETIN