Artificial Intelligence with Python
Introduction to Artificial Intelligence
This course from Harvard University explores the concepts and algorithms at
the foundation of modern artificial intelligence, diving into the ideas that give
rise to technologies like gameplaying engines, handwriting recognition, and
machine translation. You'll gain exposure to the theory behind graph search
algorithms, classification, optimization, reinforcement learning, and other
topics in artificial intelligence and machine learning. Brian Yu teaches this
course.
About the Course
Hello, world! This is CS50, and this is an introduction to artificial intelligence with
Python with CS50's own Brian Yu. This course picks up where CS50 itself leaves off
and explores the concepts and algorithms at the foundation of modern AI.
We'll start with a look at how AI can search for solutions to problems, whether those
problems are learning how to play a game or trying to find driving directions to a
destination. We'll then look at how AI can represent information, both knowledge that
our AI is certain about, but also information and events about which our AI might be
uncertain, learning how to represent that information, but more importantly, how to use
that information to draw inferences and new conclusions as well.
We'll explore how AI can solve various types of optimization problems, trying to
maximize profits or minimize costs or satisfy some other constraints before turning our
attention to the fast-growing field of machine learning, where we won't tell our AI
exactly how to solve a problem, but instead, give our AI access to data and experiences
so that our AI can learn on its own how to perform these tasks.
In particular, we'll look at neural networks, one of the most popular tools in modern
machine learning, inspired by the way that human brains learn and reason as well before
finally taking a look at the world of natural language processing so that it's not just us
humans learning to learn how artificial intelligence is able to speak, but also AI learning
how to understand and interpret human language as well.
We'll explore these ideas and algorithms, and along the way, give you the opportunity to
build your own AI programs to implement all of this and more. This is CS50.
Introduction to Artificial Intelligence
This course from Harvard University explores the concepts and algorithms at
the foundation of modern artificial intelligence, diving into the ideas that give
rise to technologies like gameplaying engines, handwriting recognition, and
machine translation. You'll gain exposure to the theory behind graph search
algorithms, classification, optimization, reinforcement learning, and other
topics in artificial intelligence and machine learning. Brian Yu teaches this
course.
About the Course
Hello, world! This is CS50, and this is an introduction to artificial intelligence with
Python with CS50's own Brian Yu. This course picks up where CS50 itself leaves off
and explores the concepts and algorithms at the foundation of modern AI.
We'll start with a look at how AI can search for solutions to problems, whether those
problems are learning how to play a game or trying to find driving directions to a
destination. We'll then look at how AI can represent information, both knowledge that
our AI is certain about, but also information and events about which our AI might be
uncertain, learning how to represent that information, but more importantly, how to use
that information to draw inferences and new conclusions as well.
We'll explore how AI can solve various types of optimization problems, trying to
maximize profits or minimize costs or satisfy some other constraints before turning our
attention to the fast-growing field of machine learning, where we won't tell our AI
exactly how to solve a problem, but instead, give our AI access to data and experiences
so that our AI can learn on its own how to perform these tasks.
In particular, we'll look at neural networks, one of the most popular tools in modern
machine learning, inspired by the way that human brains learn and reason as well before
finally taking a look at the world of natural language processing so that it's not just us
humans learning to learn how artificial intelligence is able to speak, but also AI learning
how to understand and interpret human language as well.
We'll explore these ideas and algorithms, and along the way, give you the opportunity to
build your own AI programs to implement all of this and more. This is CS50.
