Computer Science

This course provides an overview of the fundamental principles and important applications of computer vision. Topics include image processing, segmentation, feature extraction, photometric vision, motion and tracking, camera models, scene reconstruction, and human/scene/object recognition and detection.

This introductory course addresses basic concepts and linguistic processing methods regarding natural language comprehension and machine translation. It discusses fundamental concepts in information retrieval, text processing, and natural language understanding. Specific topics include morphological analysis, syntactic parsing, semantic analysis, pragmatics, and language generation.

Automatic methods of Information Retrieval (IR) have gained greater significance in recent years due to the dramatic increase in the amount of data available on the Web. The data is often present in multiple forms (such as text, image, video) and hence it is necessary that the IR techniques being deployed on the web are able to perform various operations such as search and retrieval across all these different data formats. In this course, the study of IR is focused on the methodologies of indexing, processing, and querying of primary textual data and extended to video and image data in the latter part of the course.

Decentralized blockchain-based systems, such as Bitcoin and Ethereum, are successful beyond all expectations. Although still in their infancy, they promise to revolutionize how we think of financial, information, and other infrastructures. This course covers the technical aspects of public distributed ledgers, blockchain systems, cryptocurrencies, and smart contracts. It covers how these systems are built, how to interact with them, and how to design and build secure distributed applications.

This course offers a study of the fundamentals of computers. Topics include: machine and assembly language; processor design; memory system of a computer.

This course examines the design, the architecture and the development of web applications using technologies currently popular in the marketplace including Java and . NET environments. There are three key themes examined in the unit: Presentation layer, Persistence layer, and Interoperability. The course will examine practical technologies such as JSP and Servlets, the model-view-controller (MVC) architecture, database programming with ADO. NET and JDBC, advanced persistence using ORM, XML for interoperability, and XML-based SOAP services and Ajax, in support of the theoretical themes identified. 

This class solves problems by implementing sensors, algorithms, and actions. The process of solving problems (system proposal, design, implementation, evaluation, discussion, issue derivation and correction, implementation of final results) is carried out in stages through the project, and the systematic problem-solving process is learned through communication between team members. 

This course covers the basic theories and techniques for matrix computations and linear algebra with a focus on topics including systems of equations, vector spaces, determinants, eigenvalues, QR decomposition, and least squares.

This course examines search methods; knowledge representation using logic and probability; planning and decision making under uncertainty; and machine learning.