Introduction to Artificial Intelligence
Exploring Concepts and Algorithms
Course Overview
- Learn concepts and algorithms at the foundation of modern artificial intelligence
- Gain exposure to graph search algorithms, classification, optimization, and more
- Explore machine learning, neural networks, and natural language processing
- Taught by Brian Yu from Harvard University
Introduction to AI
- AI encompasses technologies like game-playing engines, handwriting recognition, and machine translation
- Graph search algorithms, classification, and optimization are key components of AI
- Reinforcement learning and machine learning enable AI to learn and improve over time
- Neural networks, inspired by human brains, are popular tools in modern AI
Search Algorithms
- AI searches for solutions to problems, such as finding driving directions or playing games
- States represent configurations of the agent in its environment
- Actions are choices that can be made in a given state
- Transition model defines the result of applying an action in a state
Optimization and Machine Learning
- Optimization problems aim to maximize profits, minimize costs, or satisfy constraints
- Machine learning enables AI to learn from data and experiences
- Neural networks, inspired by the human brain, are powerful tools in machine learning
- Natural language processing enables AI to understand and interpret human language
Conclusion
- Artificial intelligence encompasses a wide range of technologies and algorithms
- AI enables machines to perform tasks that require intelligent and rational behaviors
- In this course, students will explore key concepts in AI and gain hands-on experience
- Build your own AI programs and dive into the world of artificial intelligence