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Chemistry |
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CHEM 000/6107 - Chemistry of Natural and Synthetic Polymers (3 cr.)
Prerequisites
Description Synthesis and characterization of natural and synthetic polymers, their applications in drug delivery systems, food and goods storage and packaging, polymer nanocomposites, polymeric membranes.
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Comparative Religion |
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CREL 529/5609 - World Religions and the Study of Religion (3 cr.)
Prerequisites Prerequisite: Enrollment in the Islamic Studies MA program.
Description This course will introduce students to the great world religions other than Islam, and will introduce them to current theories and methods in the academic field of Religious Studies.
Cross-listed Same as .
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Computer Science and Engineering |
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CSCE 110/1101 - Fundamentals of Computing II (3 cr.)
Prerequisites CSCE 1001 and concurrent with CSCE 1102
ECNG students not required to take CSCE 1102
Description Introduces concepts and techniques for developing larger software systems. The object-oriented paradigm is further utilized using a modern programming language such as Java or C++. Covers topics that include classes and objects, inheritance, encapsulation, polymorphism, more algorithms, basic design patterns, generics, testing. Also covers the design and implementation of data structures including but not limited to lists, trees, and graphs.
When Offered Offered in fall and spring.
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CSCE 456/4502 - Design of Web-based Systems (3 cr.)
Prerequisites CSCE 2501 or MOIS 3201 *
*for MICT students only
Description Introduction to the Web as a platform, the Web as an n-tier client-server architecture, basic components of a web-based application, developing static and dynamic web pages. Enhancing Web pages using Scripting languages. Developing Web-based applications. Using Server-extension techniques and tools. Introduction to XML and its associated technologies. Emerging technologies and tools on the web. Wireless Web protocols and techniques.
When Offered Offered in fall
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CSCE 000/4604 - Practical Machine Deep Learning (3 cr.)
Prerequisites CSCE 2202
MACT 1122
Description Supervised and Unsupervised learning, Logistic and soft-max regression, Perception and multilayer neural networks, Back-propagation, Convolutional Neural Network (CNN), Recurrent Neural Network, Generative models, Reinforcement Learning, case studies.
Check course scheduling information
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