Provides an overview of modern microprocessor design. The topics covered in the course will include the design of super-scalar processors and their memory systems, and the fundamentals of multi-core processor design. Prerequisite: CS 3330 with a grade of C- or better

This course explores Natural Language Processing (NLP), examining how computers are trained to understand and process human language. Students will gain a thorough understanding of both core NLP concepts and advanced techniques, including text analysis, language modeling, machine translation, question answering, text generation, conversation modeling, and the latest advancements in large language models. Prerequisite: CS 3100 with a grade of a C- or better and APMA 3080 or equivalent.

This course aims to give an introduction to basic ideas and concepts of RL while avoiding deep dive in mathematical treatments. The course will help the student build an intuitive understanding of RL and give students hands-on experience on small-scale RL problems. Prerequisite: CS 2100 with a grade of C- or better or successfully complete the CS 2100 place out test.

This course is a general introduction to cryptocurrencies and blockchain applications. Students will understand the theoretical concepts that underlay cryptocurrencies, and implement both their own cryptocurrencies as well as develop applications that run on existing cryptocurrencies. Students will see the ethics, legal, and policy aspects pertaining to the subject. Prerequisite: CS 3100 with a grade of C- or better

Supports the writing of the technical report component of the fourth-year thesis, credit for which is given in STS 4600. Students will write the report assuming a non-technical audience. The course is part of the CS 4XXX elective option in the fourth-year CS thesis track. Student must be a 4th Year BS Computer Science (First or Second Major) and must have completed or be currently enrolled in STS 4500

Required for Distinguished Majors completing the Bachelor of Arts degree in the College of Arts and Sciences. An introduction to computer science research and the writing of a Distinguished Majors thesis. Prerequisites: CS 3100 with a grade of C- or higher, and a BACS major

This course explores Natural Language Processing (NLP), examining how computers are trained to understand and process human language. Students will gain a thorough understanding of both core NLP concepts and advanced techniques, including text analysis, language modeling, machine translation, question answering, text generation, conversation modeling, and the latest advancements in large language models.

This course focuses on the core principles of RL. Like statistical learning, a central challenge of RL is to generalize learned capabilities to unseen environments. However, RL faces additional challenges such as exploration-exploitation tradeoff, credit assignment, and distribution mismatch between behavior and target policies. Throughout the course, we will delve into various solutions to these challenges and provide theoretical justifications.

This course is designed to develop cross-competency in the technical, analytical, and professional capabilities necessary for the emerging field of Cyber-Physical Systems (CPS). It provides convergence learning activities based around the applications, technologies, and system designs of CPS as well as exploring the ethical, social, and policy dimensions of CPS work. The course also emphasizes the importance of communication as a necessary skill.

A graduate student returning from Curricular Practical Training can use this course to claim one credit hour of academic credit after successfully reporting, orally and in writing, a summary of the CPT experience to his/her academic advisor.