ISE 383 - Data Analytics and Artificial Intelligence

This course introduces students to the principles and practices of data analytics, statistical learning, and artificial intelligence. Core topics include intelligent agents, problem-solving with search, probabilistic reasoning, neural networks, supervised learning (regression, classification, tree-based methods), and unsupervised learning (clustering, dimensionality reduction). Emphasis is placed on both the theory and practical implementation of these methods using Python and industry-standard tools. Students gain hands-on experience through practice sessions, assignments, and a team-based project where they design and present an AI-driven solution to a real-world problem. The course emphasizes critical thinking, problem-solving, and applied analytics, ensuring students understand both the limitations and opportunities of modern AI methods.

Prerequisites & Notes: ISE 301 and ISE 310
Credits: 4
Grade Mode: Letter