This course provides a foundational understanding of Artificial Intelligence, covering key concepts, techniques, and real-world applications. Students will explore AI history, problem-solving methods, machine learning, and ethical considerations. Hands-on exercises will reinforce AI principles using practical tools.
Module Outline:
Introduction to AI – History, definitions, and key AI domains.
Problem-Solving & Search Algorithms – Heuristic search, A*, and adversarial search.
Knowledge Representation & Reasoning – Logic, ontologies, and inference.
Machine Learning Fundamentals – Supervised vs. unsupervised learning and key algorithms.
Neural Networks & Deep Learning – Basics of neural networks and deep learning models.
AI Ethics & Bias – Responsible AI, fairness, and societal impacts.
AI Applications & Future Trends – Real-world AI use cases and emerging technologies.
