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CS221: Artificial Intelligence: Principles and Techniques. Instructors: Prof. Percy Liang and Prof. Dorsa Sadigh, Department of Computer Science, Stanford University.
527 years, 8 months
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What do web search, speech recognition, face recognition, machine translation, autonomous driving, and automatic scheduling have in common? These are all complex real-world problems, and the goal of artificial intelligence (AI) is to tackle these with rigorous mathematical tools. In this course, you will learn the foundational principles that drive these applications and practice implementing some of these systems. Specific topics include machine learning, search, game playing, Markov decision processes, constraint satisfaction, graphical models, and logic. The main goal of the course is to equip you with the tools to tackle new AI problems you might encounter in life. You can find more information about this course, such as lecture slides and syllabus, here. (from Stanfordonline)
Course Currilcum
- Lecture 01 – Overview Unlimited
- Lecture 02 – Machine Learning: Linear Classifiers, GSD Unlimited
- Lecture 03 – Machine Learning: Features, Neural Networks Unlimited
- Lecture 04 – Machine Learning: Generalization, K-means Unlimited
- Lecture 05 – Search: Dynamic Programming, Uniform Cost Search Unlimited
- Lecture 06 – Search: A* Unlimited
- Lecture 07 – Markov Decision Processes: Value Iteration Unlimited
- Lecture 08 – Markov Decision Processes: Reinforcement Learning Unlimited
- Lecture 09 – Game Playing: Minimax, Alpha-beta Pruning Unlimited
- Lecture 10 – Game Playing: TD Learning, Game Theory Unlimited
- Lecture 11 – Factor Graphs: Constraint Satisfaction Problems Unlimited
- Lecture 12 – Factor Graphs: Conditional Independence Unlimited
- Lecture 13 – Bayesian Networks: Inference Unlimited
- Lecture 14 – Bayesian Networks: Forward-Backward Unlimited
- Lecture 15 – Bayesian Networks: Maximum Likelihood Unlimited
- Lecture 16 – Logic: Propositional Logic Unlimited
- Lecture 17 – Logic: First-Order Logic Unlimited
- Lecture 18 – Deep Learning Unlimited
- Lecture 19 – Conclusion Unlimited
