This course introduces the foundational principles and techniques of Artificial Intelligence (AI) and Data Science (DS). Topics include data collection, cleaning, preprocessing, and visualization; essential data science methodologies (regression, classification, clustering, and artificial neural networks); problem-solving using search algorithms; knowledge representation, reasoning, machine learning basics, and natural language processing. Through hands-on projects, the course emphasizes real-world applications of AI in various domains with a broad overview of AI concepts and their practical use cases. Students will also explore the ethical implications of AI and gain practical experience implementing AI techniques.
P: MATH 320 and COMP SCI 351 with at least C grades in both
Fall Only.