Number of Credit Hours
16 Credit Hours
Around 4-6 Courses
Courses You Could Take
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This course will cultivate critical thinking skills by presenting computer science as problem solving discipline with emphasis in: fundamentals of computer science, algorithm development, coding, debugging and documentation of programs. The course will also include hands-on activities through assigned programming work.
Hours:
4
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The course offers an introduction to information discovery from including but not limited to text, sound, images, videos, business data, as well as chemical and biological sequences. Students will develop an understanding of digital information processing (DIP) theories, and obtain hands-on experience in using and implementing fundamental DIP algorithms. It covers topics on discrete-time linear systems, analog-to-digital and digital-to-analog conversion, time-to-frequency and frequency-to-time transforms, digital filter design, and spectral analysis.
Prerequisite/Corequisite:
Prerequisite: CSCI 1301 or CSCI 1371
Hours:
3
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Machine learning is now incredibly fast growing, with its applications ranging from business intelligence to homeland security, from analyzing medical images to monitoring aging bridges, from self-driving automobiles to astrophysics, etc. This course is an introduction to the fundamental and modern machine learning techniques. Students will learn the concepts of machine learning algorithms and gain hands-on experience in applying them to solve various data analysis problems. It is valuable to students who are interested in robotic vision, engineering, data science and intelligent computing applications. Credit will not be awarded for more than one of the following courses: CYBR 4850 or CSCI 4840.
Prerequisite/Corequisite:
Prerequisites: MATH 1450 and either CSCI 1301 or CSCI 1371 (for non-Computer Science majors), all with grades of C or higher
Hours:
3
View Course in Catalog
