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CSC425 - Principles of Machine Learning
Course Description
This course offers a thorough exploration of machine learning principles and practical application using Azure technologies. Students will grasp fundamental machine learning concepts and delve into supervised and unsupervised learning. Through hands-on exercises, participants will gain practical insights into model training, validation, and evaluation techniques. The emphasis is on developing practical skills, including utilizing Azure Machine Learning Studio for designing and deploying experiments, implementing feature engineering, and optimizing models for scalability and efficiency in the Azure environment. Upon completion, participants will possess the knowledge and hands-on experience to proficiently navigate and leverage Azure Machine Learning for effective machine learning solutions.
Credit Hours: 3
CSC430 - Principles of Robotic Theory
Course Description
This course provides an introduction to the theories associated with robotic systems in computing. Students will gain an understanding of basic principles and methodologies associated with robotics and robot control systems. Students will student robot mechanics, intelligent controls, and dynamics. Prerequisite Course: CSC410.Â
Credit Hours: 3
CSC435 - Fundamentals of Information Retrieval and Web Searching
Course Description
The course provides an introduction to the processes and principles of information retrieval and web searching. Students will explore problems in natural language processing that apply to web searching and other information retrieval systems. The course will focus on understanding efficient text indexing, document clustering and classification, and machine-learning based ranking.
Credit Hours: 3
CSC410 - Artificial Intelligence
Course Description
This course introduces the basic concepts associated with Artificial Intelligence (AI) including heuristic search procedures associated with general graphs. Students will develop an understanding of knowledge representation and techniques associated with AI reasoning with uncertainty with the goal of solving current-day complex problems within an organization. Emphasis will be on applying propositional logic, Bayesian probability analysis, and machine learning concepts to solve computationally-intensive problem.Â
Credit Hours: 3
CSC415 - Computer Vision
Course Description
This course provides an introduction to concepts involved in the application of computer vision theory. In this course, students will gain an understanding of the use of cameras and projection models for completing image processing. Students will be introduced to various techniques, including filtering, edge detection, segmentation, and clustering.
Credit Hours: 3
