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    Machine Learning Minor

    The machine learning minor is primarily designed for computer science and cybersecurity students. Students in other majors at UNG in which a minor is an option can complete this minor as well. This program is 15 credit hours and requires a grade of C or higher in the required courses to complete.

    • Catalog Listing

    Number of Credit Hours

    16 Credit Hours

    Around 4-6 Courses

    Courses You Could Take

    • CSCI 1301 - Computer Science I

      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



      View Course in Catalog

    • CSCI 4810 - Digital Information Processing

      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



      View Course in Catalog

    • CSCI 4840 - Machine Learning

      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

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