This course introduces the foundational concepts, algorithms, and applications of artificial intelligence. It covers problem-solving, machine learning, knowledge representation, and reasoning techniques used to build intelligent and autonomous systems.
Fundamental Topics
Covers AI basics, history, problem-solving, search algorithms, knowledge representation, reasoning, and introductory machine learning concepts.
AI problem-solving
Search algorithms
Knowledge representation
Intermediate Topics
Focuses on advanced machine learning, neural networks, NLP, computer vision, reinforcement learning, and AI applications.
Machine learning basics
Neural networks
Natural language processing
Advanced Topics
Includes deep learning, generative AI, robotics, multi-agent systems, AI optimization, ethical considerations, and cutting-edge research.
Autonomous agents
Multi-agent systems
Ethical AI
Course Outcomes
Enable students to design, implement, and evaluate AI solutions across diverse real-world problems effectively.