This course explores theoretical and practical approaches toward building human-level intelligence in machines. Topics include cognitive architectures, transfer learning, self-learning systems, and the ethical and safety challenges associated with general-purpose AI.
Fundamental Topics
Covers AGI concepts, history, intelligence theories, learning paradigms, reasoning, problem-solving, and foundational AI principles.
Human cognition models
AI architectures
Learning paradigms
Intermediate Topics
Focuses on cognitive architectures, transfer learning, multi-domain reasoning, adaptive learning, and AGI system design approaches.
Transfer learning
Meta-learning
Cognitive AI
Advanced Topics
Includes human-level intelligence modeling, autonomous decision-making, ethical considerations, self-improving systems, and cutting-edge AGI research.
Self-learning systems
AGI safety
Consciousness modeling
Course Outcomes
Enable students to design, analyze, and implement intelligent systems approaching human-level general intelligence effectively.